CN112231672A - Identity recognition method and device - Google Patents
Identity recognition method and device Download PDFInfo
- Publication number
- CN112231672A CN112231672A CN202011193861.8A CN202011193861A CN112231672A CN 112231672 A CN112231672 A CN 112231672A CN 202011193861 A CN202011193861 A CN 202011193861A CN 112231672 A CN112231672 A CN 112231672A
- Authority
- CN
- China
- Prior art keywords
- identity recognition
- target object
- identity
- recognition model
- target
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/31—User authentication
- G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/08—Insurance
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Finance (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Accounting & Taxation (AREA)
- Computer Security & Cryptography (AREA)
- Life Sciences & Earth Sciences (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Bioinformatics & Computational Biology (AREA)
- Computer Hardware Design (AREA)
- Software Systems (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Evolutionary Biology (AREA)
- Development Economics (AREA)
- Economics (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- Technology Law (AREA)
- General Business, Economics & Management (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
The embodiment of the specification provides an identity recognition method and an identity recognition device, wherein the identity recognition method comprises the following steps: downloading an identity recognition model aiming at a target object from a server according to a preset downloading address under the condition that a display page of the target item is monitored to be a preset page; and performing identity recognition on the acquired biological characteristic image of the target object through the identity recognition model to obtain an identity recognition result of the target object.
Description
Technical Field
The embodiment of the specification relates to the technical field of computers, in particular to an identity recognition method and device.
Background
With the development of information technology, the identification information authentication and management of animals are increasingly regarded by the public, and in many animal-oriented fields or services, the identification information authentication and management of animals are indispensable parts of the fields or services, such as pet insurance, identification of animal authentication, scientific research management, rare species tracking, and the like.
However, the core of identity information authentication and identity information management for animals is precise identity identification for animals. Only on the basis of accurately identifying the identity of an animal, the identity information authentication and identity information management of the animal can be effectively enhanced, so that better and personalized services or researches are provided for the animal, but at present, chips are mostly implanted into the animal body for identifying the identity of the animal, so that the technical difficulty is high, the user experience is poor, and the cost is high, so that a more effective method is urgently needed for solving the problems.
Disclosure of Invention
In view of this, the embodiments of the present specification provide an identity recognition method. One or more embodiments of the present disclosure also relate to an identification apparatus, a computing device, and a computer-readable storage medium to solve the technical problems in the prior art.
In a first aspect of embodiments of the present specification, an identity recognition method is provided, including:
downloading an identity recognition model aiming at a target object from a server according to a preset downloading address under the condition that a display page of the target item is monitored to be a preset page;
and performing identity recognition on the acquired biological characteristic image of the target object through the identity recognition model to obtain an identity recognition result of the target object.
In a second aspect of embodiments of the present specification, there is provided an identification apparatus, including:
the downloading module is configured to download the identity recognition model aiming at the target object from the server according to a preset downloading address under the condition that the display page of the target item is monitored to be a preset page;
and the identification model is configured to identify the acquired biological characteristic image of the target object through the identification model to obtain an identification result of the target object.
In a third aspect of embodiments of the present specification, there is provided a computing device comprising:
a memory and a processor;
the memory is to store computer-executable instructions, and the processor is to execute the computer-executable instructions to:
downloading an identity recognition model aiming at a target object from a server according to a preset downloading address under the condition that a display page of the target item is monitored to be a preset page;
and performing identity recognition on the acquired biological characteristic image of the target object through the identity recognition model to obtain an identity recognition result of the target object.
In a fourth aspect of the embodiments of the present specification, a computer-readable storage medium is provided, which stores computer-executable instructions that, when executed by a processor, implement the steps of the identification method.
The specification provides an identity recognition method, which downloads an identity recognition model for a target object from a server according to a preset download address under the condition that a display page of the target item is monitored to be a preset page, realizes downloading of the identity recognition model under the condition that a user is monitored to have a recognition intention, greatly avoids waste of download resources, performs identity recognition on an acquired biological characteristic image of the target object through the identity recognition model to obtain an identity recognition result of the target object, avoids identity recognition on the target object at the server, reduces the recognition pressure of the server, provides an identity recognition method for the target object based on biological characteristics for the target item, and increases the safety of the target item.
Drawings
FIG. 1 is a flow chart of a process for a method of identification provided in one embodiment of the present description;
FIG. 2 is a flowchart illustrating a process for identifying a pet in a pet insurance project according to an embodiment of the present disclosure;
fig. 3 is a process flow diagram of an identification method applied to animal husbandry insurance program according to an embodiment of the present disclosure;
FIG. 4 is a schematic diagram of an identification device provided in an embodiment of the present disclosure;
fig. 5 is a block diagram of a computing device according to an embodiment of the present disclosure.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present description. This description may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, as those skilled in the art will be able to make and use the present disclosure without departing from the spirit and scope of the present disclosure.
The terminology used in the description of the one or more embodiments is for the purpose of describing the particular embodiments only and is not intended to be limiting of the description of the one or more embodiments. As used in one or more embodiments of the present specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used in one or more embodiments of the present specification refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It will be understood that, although the terms first, second, etc. may be used herein in one or more embodiments to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first can also be referred to as a second and, similarly, a second can also be referred to as a first without departing from the scope of one or more embodiments of the present description. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
First, the noun terms to which one or more embodiments of the present specification relate are explained.
The pet insurance: pet insurance refers to the act of insuring an insurer to pay a premium for an insured pet pursuant to a contractual agreement, the insurer assuming a commercial insurance action for paying a premium when the insured pet dies, becomes disabled, ill, or reaches the contractual age, deadline for the insured pet to injure or lose the pet due to a possible accident of the contractual agreement.
Pet file: the pet information file comprises pet name, pet nose print, pet type, birth year and month, past medical history and the like.
Identifying the pet nose print: the unique identity of the pet is identified by identifying the unique nasal print of the pet.
APP: generally referred to as cell phone software. The mobile phone software mainly refers to software installed on a smart phone, and overcomes the defects and individuation of an original system. The mobile phone is improved in functions, and a main means of richer use experience is provided for users.
Js: the deep learning framework of the Google open source can meet the intelligent capability requirements such as identification and the like based on the framework.
Javascript: the script language can be run on a browser, and can realize some functional logics, style modification and the like of a page.
HTML 5: is a language description way for constructing Web content. HTML5 is the next generation standard for the internet, a language way to build and present internet content. HTML was generated in 1990, 1997, HTML4 became the internet standard and was widely used in the development of internet applications.
In the present specification, an identification method is provided, and one or more embodiments of the present specification relate to an identification apparatus, a computing device, and a computer-readable storage medium, which are described in detail in the following embodiments one by one.
The embodiment of the identity recognition method provided by the specification is as follows:
fig. 1 shows a processing flow chart of an identity recognition method according to an embodiment of the present specification, which specifically includes the following steps:
and 102, downloading the identity recognition model aiming at the target object from the server according to a preset downloading address under the condition that the display page of the target item is monitored to be a preset page.
Specifically, a target subject includes an animal including, but not limited to, a wild animal or an animal feed, wherein feeding is feeding, domesticating, or raising; livestock includes animals fed or raised by users, including animal pets (pet dogs, pet cats, pet pigs, etc.), tea pet pets (bombesi, fabusia, etc.), and other pets (woodchuck, rabbits, hamsters, hedgehog, bats, etc.), etc., and in addition to the above-mentioned pets, livestock also includes poultry animals raised in livestock industry, such as chickens, ducks, etc., or animals raised in animal husbandry, such as cows, sheep, horses, etc.
Accordingly, the target item includes: in practical application, in order to facilitate management of the target object, an identity archive needs to be established for the target object so as to store information of the target object, and when the target object provides service, the identity of the target object is firstly identified, so that more accurate and faster service is provided for the target object.
In specific implementation, because many target projects need to be released in a plurality of different APPs to increase the participation number of target objects of the target projects, if the identity recognition of the target objects in the target projects is realized at the server, not only is the recognition pressure of the server increased, but also development cost is needed for the identity recognition of different APPs, in the embodiment of the present specification, based on the fact that in the prior art, a small program or an APP page is usually adopted to carry the operation of the target projects, and the small program or the APP (realized by using the HTML5 technology) is used as a carrier of a presentation page of the target projects, and the upper layer of the carrier runs a deep learning frame of tensrflow.js, so that the identity recognition model for the target objects, which is trained in advance, can be downloaded on the presentation page of the target projects, so that the intelligent terminal running the target projects can identify the target objects through the identity recognition model, the development cost of developing and identifying interfaces for different APPs is saved, and the identification pressure of the server is reduced.
The identity recognition model is an algorithm model used for performing identity recognition on identity characteristics (namely biological characteristics) of a target object, the identity characteristics of the target object comprise biological characteristics such as a nose print characteristic and a palm print characteristic, the biological characteristics can be used for uniquely identifying the identity of the target object, the identity recognition model is stored in a server side and a storage position is issued to a client side in a downloading address mode during specific implementation, and the client side can download the identity recognition model from the server side through the storage position pointed by the downloading address.
It should be noted that, in order to avoid increasing the complexity of the user's operation of identifying the identity of the target object, the user may be monitored through accessing the page, and if the display page of the target item (i.e., the page accessed by the user in the target item) is a preset page (i.e., the user has an identification intention), the identity identification model is directly downloaded from the server, where the preset page includes: a biometric acquisition page, an identity entry page, an identity recognition page, and the like, without limitation.
In practical application, when a user participates in a target project, an identity archive needs to be established for a target object, and in the process of establishing the identity archive, identity recognition needs to be performed on the target object so as to record identity information of the target object, so that when a display page of the target project is an identity entry page (i.e., a page for identity entry when the identity archive is established), an identity recognition model is downloaded from a server so as to record the identity information of the target object more accurately.
Receiving a participation request submitted by a user aiming at the target project;
displaying an identity entry page for the target object based on the participation request;
under the condition that the identity input page is monitored to be the preset page, downloading an identity recognition model aiming at a target object from a server according to a preset downloading address, wherein the identity recognition model comprises: a first identity recognition model.
Specifically, the participation request refers to a request that a user is an animal and applies for participation in a project service provided in a target project, for example, a participation request for participating in a pet insurance or pet medical project, and after receiving the participation request of the user, an identity entry page (for obtaining identity information of the target object) for the target object is displayed to the user, so that an identity file is established for the target object based on the identity information entered on the identity entry page.
The first identity recognition model is a feature extraction model and is used for extracting the identity features of the target object. It should be noted that, in the process of establishing the identity archive for the target object, the downloaded first identity recognition model is used to extract the identity features of the target object, so as to store the identity features of the target object, and is used to subsequently perform feature comparison on the acquired identity features of the target object, so as to recognize whether the target object is a corresponding target object in the identity archive.
Taking the target item as the pet insurance item as an example, receiving a participation request of a user for the pet insurance item, and displaying a pet filing page to the user based on the participation request, specifically, the pet filing page includes: the method comprises the steps that information such as pet names, pet types, birth years and months, past medical histories, pet nose prints and the like is input into an interface, after a user enters a pet filing page, the pet filing page is monitored to be a preset page with identification intention, a nose print feature extraction model is downloaded from a server side of a pet insurance project according to a preset model downloading address, so that the nose print feature of a pet can be extracted (namely, the pet nose print is identified), and a pet file is established.
In addition, after the user enters the nose print entry page, the nose print feature extraction model can be downloaded from the server side of the pet insurance project according to the preset model download address, namely, the nose print entry page is used as the preset page with identification intention.
In addition, after the target object is archived, when the target object is provided with a service, the identity of the target object needs to be identified to identify whether the served target object is the target object specified in the archiving, so that when the presentation page of the target object is the identity identification page, the identity identification model is downloaded from the server to identify the identity of the target object, so as to determine whether the target object is the target object pre-recorded in the target item, in an optional implementation manner provided in this specification, when the presentation page of the target item is monitored to be a preset page, the identity identification model for the target object is downloaded from the server according to a preset download address, which is specifically implemented in the following manner:
receiving a project processing request of a user for the target project;
displaying an identification page aiming at the target object based on the project processing request;
under the condition that the identification page is monitored to be the preset page, downloading an identification model aiming at a target object from a server according to a preset downloading address, wherein the identification model comprises: a first identity recognition model and a second identity recognition model.
Specifically, the item processing request refers to a request for requesting a target object to perform an item service, such as a claim settlement request of a pet insurance item or a medical request of a pet medical item, and after receiving an item processing request submitted by a user, an identification page for the target object is presented to the user so as to identify whether the target object requested to perform the item processing is a target object recorded in the target item.
The second identity recognition model is used for comparing the identity characteristics of the target object, so as to judge whether the target object is the target object recorded in the target item.
Taking the target item as the pet insurance item as an example, receiving a claim request of a user for the pet insurance item, and displaying a pet identification page to the user based on the claim request, specifically, the pet identification page includes: the entry interface of pet nose print information, after the user gets into the pet identification page, monitor that the pet identification page is the preset page that has the discernment intention, then download the address according to preset model, download the nose print feature extraction model from the server side of pet insurance project to and nose print feature identification model, so that on the basis of extracting the nose print feature to the nose print of pet, compare with the nose print feature of the record in the pet archives that the user set up for the pet in advance, thereby whether the pet of discernment claim is the pet of guarantee in the pet insurance.
In practical applications, it is also possible that an identity recognition model of a target object has already been downloaded by an intelligent terminal of a target item, and in order to avoid repeated downloading of the identity recognition model, which may cause waste of storage resources and network resources of the intelligent terminal, an optional implementation manner provided in an embodiment of this specification further includes, when a display page of the target item is monitored to be a preset page:
judging whether the identity recognition model exists in a storage space corresponding to the display page or not;
if so, indicating that an identity recognition model already exists in the intelligent terminal for carrying the operation of the target project, and executing step 104;
if not, the intelligent terminal which bears the target project operation is indicated not to download the identity recognition model, and the step of downloading the identity recognition model aiming at the target object from the server according to the preset download address is executed.
Specifically, the storage space corresponding to the display page may be understood as a browser cache, or a hardware storage space corresponding to the target item in the intelligent terminal, which is not limited herein, and if the downloaded identity recognition model is stored in the browser cache, whether the identity recognition model exists is searched in the browser cache, and if the downloaded identity recognition model is stored in the hardware storage space, whether the identity recognition model exists is searched in the hardware storage space.
In specific implementation, the storage space can be searched according to a model identifier (unique identifier for the model) or a model name of the identity recognition model, so as to determine whether the downloaded identity recognition model exists in the storage space, and if so, the identity recognition model does not need to be downloaded again and the step 104 is directly executed, which indicates that the identity recognition model exists in the intelligent terminal for carrying the target project to operate; if not, the intelligent terminal which bears the target project operation is indicated to not download the identity recognition model, the identity recognition model still needs to be downloaded, and the step of downloading the identity recognition model aiming at the target object from the server according to the preset download address is executed.
In addition, in a case where the identification model is downloaded, there is also a case where the server updates the identification model, and since the updated identification model is generally more accurate or has other advantages than identification of the identification model before being updated, the identification model needs to be downloaded again when it is determined that the downloaded identification model is not the latest version, in an optional implementation manner provided in this specification, when it is monitored that the display page of the target item is a preset page, the method further includes:
determining version information of the identity recognition model;
under the condition that the storage space has the target identity recognition model, acquiring target version information of the target identity recognition model in the storage space;
judging whether the target version information is consistent with the version information of the identity recognition model or not;
if so, indicating that the target identity recognition model is the identity recognition model of the latest version, taking the target identity recognition model as the identity recognition model, and executing the step 104;
if not, the target identification model is the identification model before updating, then step 102 is executed.
Specifically, the version information refers to information for identifying an updated version of the identification model; the target identity recognition model refers to an identity recognition model stored in a storage space, and the target version information of the target identity recognition model is the version information for identifying the target identity recognition model, and the version information of the identity recognition model is the version information for identifying the identity recognition model stored by the server.
In specific implementation, under the condition that a display page of a target item is monitored to be a preset page, determining version information of an identity recognition model of a current server, comparing target version information of a target identity recognition model of a storage space in an intelligent terminal with version information of the identity recognition model of the server, judging whether the target version information of the target identity recognition model is consistent with the version information of the identity recognition model of the server, if so, indicating that the target identity recognition model stored in the storage space is the latest version of the identity recognition model, taking the target identity recognition model as the identity recognition model, and executing step 104; if not, the target identification model is the identification model before updating, then step 102 is executed.
For example, the version information of the identity recognition model for determining the server is as follows: v1, the storage space has a target identification model, and the obtained target version information of the target identification model is v2, therefore, the judgment result of judging whether the target version information v2 is consistent with the version information v1 is inconsistent, which indicates that the target identification model is the identification model before updating, the step of downloading the identification model for the target object from the server according to the preset download address is executed.
And 104, performing identity recognition on the acquired biological characteristic image of the target object through the identity recognition model to obtain an identity recognition result of the target object.
Specifically, on the basis of downloading the identity recognition model from the server, the identity recognition model is used for carrying out identity recognition on the biological characteristic image of the target object so as to obtain an identity recognition result of the target object.
The biometric image refers to an image containing the biometric features of the target object, such as: the identification result includes the identity feature identified in the biometric image, or the identity feature image is compared with other pre-stored identity feature images, so as to identify whether the target object is a specific target object, and the like, which is not limited herein.
In practical applications, after downloading the identification model of the target object from the server, in a process of downloading the identification model, a situation of downloading timeout may occur, and in order to avoid affecting the recognition experience of the user and avoid that the user waits too long or cannot perform identification of the target object, the obtained biometric image is uploaded to the server for identification, in an optional implementation manner provided in an embodiment of the present specification, after downloading the identification model of the target object from the server according to a preset download address, the method further includes:
displaying a downloading progress aiming at the identity recognition model;
under the condition that the downloading time length of the identity recognition model is longer than the preset time length, acquiring the biological characteristic image of the target object;
and uploading the biological characteristic image to the server, and receiving an identity recognition result aiming at the target object sent by the server.
Specifically, the download progress may be displayed in a manner of displaying a progress bar, and in addition, a download percentage and the like may also be displayed without limitation, where the preset duration refers to a preset download timeout duration, such as 10s or 20s, and the like, and is not limited herein.
For example, with the preset duration of 10s, under the condition that the download duration of the download identity recognition model exceeds 10s, obtaining a nasal print image of the pet, uploading the nasal print image of the pet to a server of the pet insurance project, and receiving a nasal print recognition result of the pet sent by the server of the pet insurance project.
In addition, a prompt whether the downloading is continued or not can be displayed to the user under the condition that the downloading is overtime, if the user selects to continue the downloading, the downloading of the identity recognition model is still carried out after the overtime, if the user selects not to continue the downloading, the obtaining of the biological characteristic image of the target object is carried out, the biological characteristic image is uploaded to the server, and the server carries out identity recognition on the target object.
Specifically, in the case that the display page is an identity entry page in step 102, that is, in the process of establishing an identity archive, in an optional implementation manner provided in the embodiment of the present specification, the identity recognition model is used to perform identity recognition on the acquired biometric image of the target object to obtain an identity recognition result of the target object, which is specifically implemented in the following manner:
acquiring the biological characteristic image of the target object;
inputting the biological characteristic image into the first identity recognition model for identity recognition to obtain reference identity characteristic information of the target object;
and uploading the reference identity characteristic information and the biological characteristic image as the identity information of the target object to the server.
The reference identity characteristic information refers to identity characteristic information which is input by a user and used for establishing an identity archive, and is used for identifying the identity of a target object.
Specifically, the identity characteristic image is input into a first identity recognition model (namely, a characteristic extraction model) to perform characteristic extraction, so as to obtain the identity characteristic (namely, reference identity characteristic information) of the target object, and the identity characteristic and the biological characteristic image are used as the identity information (information capable of uniquely identifying the target object) of the target object and uploaded to a server to be stored, so that the identity characteristic extraction of the target object is performed at an intelligent terminal which bears the operation of a target project, the identity information is stored at the server to establish an identity file of the target object, the identity of the target object is subsequently recognized, and subsequently project processing is performed on the target object on the basis of identity recognition of the target object.
In addition, in the case that the presentation page is an identification page in step 102, that is, in the process of processing the project, the identity of the target object needs to be identified so as to determine the identity of the target object, and the project service is provided for the target object based on the identity of the target object, in an optional implementation manner provided in the embodiment of this specification, the identification result of the target object is obtained by performing identification on the acquired biometric image of the target object through the identification model, and the following implementation manner is specifically adopted:
acquiring the biological characteristic image of the target object;
inputting the biological characteristic image into the first identity recognition model for identity recognition to obtain identity characteristic information of the target object;
acquiring reference identity characteristic information of the target object prestored in the server;
inputting the identity characteristic information and the reference identity characteristic information into the second identity recognition model for similarity calculation to obtain a similarity calculation result;
and determining that the identity recognition result of the target object is passed and displayed when the similarity calculation result is greater than a similarity threshold value.
The reference identity characteristic information refers to identity characteristic information entered when an identity file is established for a target object, and the similarity threshold refers to a critical value for judging whether the target object is divided into the same target object, and specifically, the value is preset according to experience or actual project scenes.
Specifically, the identity characteristic image of the acquired target object is subjected to identity characteristic extraction through a first identity identification model to obtain identity characteristic information of the target object, the extracted identity characteristic information is compared with reference identity characteristic information stored by a server side, a second identity identification model is input to obtain comparison similarity (namely a similarity calculation result), under the condition that the similarity calculation result is greater than a similarity threshold value, the target object corresponding to the biological characteristic image and the target object corresponding to the reference identity characteristic information are the same target object, namely the target object to be subjected to item processing and the target object of which the identity file is recorded before are the same target object, the identity identification result of the target object is determined to be passed through identity identification, and item processing is performed on the target item based on the identity identification result, in addition, and displaying the identification result so that the user can know the identification result aiming at the target object.
In addition, except for the case that the similarity calculation result is greater than the similarity threshold, there is also a case that the similarity calculation result is equal to or less than the similarity threshold, and in an optional implementation manner provided in an embodiment of the present specification, when the similarity calculation result is equal to or less than the similarity threshold, it is determined that the identification result of the target object is an identification failure and is displayed.
Specifically, when the similarity calculation result is less than or equal to the similarity threshold, it is indicated that the target object to be subjected to the item processing and the target object previously entered into the identity archive are not the same target object, the identity recognition result of the target object is determined to be an identity recognition failure, subsequent item processing is not performed, and the identity recognition result is displayed to remind the user to submit a correct biometric image.
In a specific implementation, the manner of obtaining a biometric image of a target object is various, and by providing various manners of obtaining a biometric image, the flexibility of obtaining a biometric image is increased, more selection manners are provided for a user, and the target object identification experience of the user is increased.
Receiving the biometric image of the target object uploaded by the user; or the like, or, alternatively,
based on an acquisition instruction submitted by the user, calling an image acquisition component to acquire the biological characteristics of the target object to obtain a biological characteristic image; or the like, or, alternatively,
and acquiring the biological characteristic image by calling the image acquisition component to scan the biological characteristic.
Specifically, the image acquisition assembly comprises a camera, a camera and the like which are connected to the intelligent shooting equipment.
The embodiments of the present description provide various ways of obtaining a biometric image, receive a biometric image that has been captured in advance and uploaded by a user, or, based on an acquisition instruction submitted by the user, invoke an image acquisition component to acquire a biometric feature of a target object (for example, by clicking a shooting control and invoking a camera to capture the biometric feature of the target object), obtain a biometric image, or scan an identity feature of the target object through the image acquisition component at preset time intervals (for example, every 300ms or every 100ms), and obtain the biometric image.
The specification provides an identity recognition method, which downloads an identity recognition model aiming at a target object from a server according to a preset download address under the condition that a display page of the target item is monitored to be a preset page, so that the identity recognition model is downloaded to an intelligent terminal bearing the target item to operate under the condition that a user is monitored to have recognition intention, the waste of download resources is greatly avoided, the obtained biological characteristic image of the target object is subjected to identity recognition through the identity recognition model to obtain an identity recognition result of the target object, the identity recognition of the target object is realized on the intelligent terminal, the recognition pressure of the server is reduced, the identity recognition of the target object is provided for the target item, and the item safety of the target item is improved.
The identity recognition method will be further described with reference to fig. 2, taking the application of the identity recognition method provided in this specification to pet filing in pet insurance projects as an example. Fig. 2 shows a processing flow chart of an identification method applied to pet filing in a pet insurance project according to an embodiment of the present specification, which specifically includes the following steps:
step 202, receiving an insurance participation request submitted by a user for a pet insurance project.
Specifically, the intelligent terminal bearing the pet insurance project receives the insurance participation request.
And step 204, displaying a pet file page aiming at the pet to the user based on the participation request.
Specifically, the pet profile page is used for receiving pet information input by a user: such as identity information, birth year and month, etc., to establish a pet file for the pet.
Step 206, receiving a nose print input instruction submitted by the user on the pet profile page.
In practical application, the nose print can be replaced by a biological characteristic such as a palm print or a voiceprint which can uniquely identify an animal.
And step 208, starting the camera and displaying an image shooting page based on the nose print input instruction.
And step 210, receiving a shooting instruction submitted by a user on the image shooting page.
And step 212, calling the camera to shoot the nasal print of the pet based on the shooting instruction to obtain the nasal print image of the pet.
And 214, submitting a downloading request to a server of the pet insurance project according to a preset downloading address under the condition that the image shooting page is monitored to be a preset page.
And step 216, receiving the identification model code downloaded for the pet from the server side of the pet insurance project based on the downloading request.
And step 218, compiling the downloaded identification model code to obtain an executable nose print feature extraction model.
In specific implementation, the downloaded recognition model code can be compiled through Tensorflow.
And step 220, inputting the nasal print image into the nasal print feature extraction model for extracting the nasal print features to obtain the nasal print features of the pet.
Specifically, the nose line feature can be understood as a texture feature of the nose line, and the shape, the depth and the color of the texture of different nose lines are gradually changed.
Step 222, establishing and displaying a pet file of the pet based on the nose print characteristics.
In summary, the present specification provides an identity recognition method, which downloads an identity recognition model for a pet from a server according to a preset download address when it is monitored that an image shooting page of a pet insurance project is a preset page, so as to download the identity recognition model to an intelligent terminal carrying a pet insurance project operation when it is monitored that a user has a recognition intention, and perform identity recognition on an acquired nose print image of the pet by using the identity recognition model to obtain a nose print feature of the pet, thereby implementing identity recognition on the pet at the intelligent terminal, reducing recognition pressure of the server, providing accurate identity recognition of the pet for the pet insurance project, and increasing project safety of the pet insurance project.
The identity recognition method provided in the present specification will be further described below with reference to fig. 3, taking as an example the application of the identity recognition method in the animal husbandry insurance program. Fig. 3 shows a processing flow chart of an identity recognition method applied to an animal husbandry insurance project according to an embodiment of the present specification, which specifically includes the following steps:
And 304, displaying an identification page of the horses guaranteed by the animal husbandry insurance project to the user based on the claim settlement request.
Specifically, the horses in the embodiments of the present specification may be replaced with other animals such as poultry and livestock that have been bred in animal husbandry secured in animal husbandry insurance projects, for example: cattle, sheep, pigs, etc.
And 306, downloading the nose print recognition model aiming at the horse from the server according to a preset download address under the condition that the identity recognition page is monitored to be the preset page.
Wherein the nose print recognition model comprises: the method comprises a nose pattern feature extraction model and a nose pattern feature identification model.
And step 310, shooting the horse based on the image acquisition instruction to obtain a nose print image of the horse.
Specifically, the nose print image can be replaced by other images such as a palm print and an iris, which can uniquely identify the biological characteristics of the animal.
And step 312, inputting the nose pattern image into the nose pattern image feature extraction model for identity recognition, and obtaining the nose pattern feature information of the horse.
And step 314, acquiring reference nose print characteristic information pre-stored in the server for the horse.
And step 316, inputting the nose pattern feature information and the reference nose pattern feature information into the nose pattern feature identification model for similarity calculation to obtain a similarity calculation result.
And 318, determining that the identification result of the horse is passed and displayed when the similarity calculation result is greater than the similarity threshold.
In summary, the present specification provides an identity recognition method, which downloads an identity recognition model for a horse from a server according to a preset download address when it is monitored that an identity recognition page of an animal husbandry insurance project is a preset page, so as to download the identity recognition model to an intelligent terminal carrying an operation of the animal husbandry insurance project when it is monitored that a user has an identification intention, and performs identity recognition on an acquired nasal print characteristic image of the horse through the identity recognition model to obtain a nasal print characteristic of the horse, thereby implementing identity recognition on the horse by the intelligent terminal, reducing recognition pressure of the server, providing accurate identity recognition of the horse for the animal husbandry insurance project, and increasing project safety of the animal husbandry insurance project.
The embodiment of the identity recognition device provided by the specification is as follows:
corresponding to the above method embodiment, the present specification further provides an identity recognition apparatus embodiment, and fig. 4 shows a schematic diagram of an identity recognition apparatus provided in an embodiment of the present specification. As shown in fig. 4, the apparatus includes:
the downloading module 402 is configured to download the identity recognition model for the target object from the server according to a preset downloading address under the condition that the display page of the target item is monitored to be a preset page;
a recognition module 404 configured to perform identity recognition on the acquired biometric image of the target object through the identity recognition model to obtain an identity recognition result of the target object.
Optionally, the downloading module 402 includes:
a first receiving request submodule configured to receive a participation request submitted by a user for the target project;
a display entry page sub-module configured to display an identity entry page for the target object based on the participation request;
a first downloading submodule configured to download, from a server, an identity recognition model for a target object according to a preset download address under the condition that it is monitored that the identity entry page is the preset page, where the identity recognition model includes: a first identity recognition model.
Optionally, the identifying module 404 includes:
a first acquisition image sub-module configured to acquire the biometric image of the target object;
a first identification submodule configured to input the biometric image into the first identity identification model for identity identification, and obtain reference identity characteristic information of the target object;
and the uploading sub-module is configured to upload the reference identity characteristic information and the biological characteristic image as the identity information of the target object to the server.
Optionally, the downloading module 402 includes:
a second receiving request submodule configured to receive a project processing request of a user for the target project;
a presentation identification page sub-module configured to present an identification page for the target object based on the item processing request;
the second downloading submodule is configured to download an identity recognition model for a target object from a server according to a preset downloading address under the condition that the identity recognition page is monitored to be the preset page, wherein the identity recognition model comprises: a first identity recognition model and a second identity recognition model.
Optionally, the identifying module 404 includes:
a second acquisition image sub-module configured to acquire the biometric image of the target object;
a second identification submodule configured to input the biometric image into the first identity identification model for identity identification, so as to obtain identity characteristic information of the target object;
the information obtaining submodule is configured to obtain reference identity characteristic information of the target object prestored in the server side;
the similarity operator module is configured to input the identity characteristic information and the reference identity characteristic information into the second identity recognition model for similarity calculation to obtain a similarity calculation result;
and the first determination result submodule is configured to determine that the identification result of the target object is passed and displayed in identification when the similarity calculation result is greater than the similarity threshold.
Optionally, the identity recognition apparatus further includes:
and the second determination result submodule is configured to determine that the identification result of the target object is identification failure and display the identification failure when the similarity calculation result is smaller than or equal to the similarity threshold.
Optionally, the identity recognition apparatus further includes:
a display progress module configured to display a download progress for the identification model;
an image acquisition module configured to acquire the biometric image of the target object when a download duration of the identification model is greater than a preset duration;
the uploading image module is configured to upload the biological characteristic image to the server and receive an identification result which is sent by the server and aims at the target object.
Optionally, the identity recognition apparatus further includes:
the judging model module is configured to judge whether the identity recognition model exists in a storage space corresponding to a display page when the display page of the target item is monitored to be a preset page;
if yes, the identification module 404 is operated;
if not, the downloading module 402 is operated.
Optionally, the identity recognition apparatus further includes:
a version information determining module configured to determine version information of the identification model;
the target version information obtaining module is configured to obtain target version information of a target identity recognition model in the storage space under the condition that the target identity recognition model exists in the storage space;
the version judging module is configured to judge whether the target version information is consistent with the version information of the identity recognition model;
if so, the target identity recognition model is used as the identity recognition model, and the recognition module 404 is operated;
if not, the downloading module 402 is operated.
Optionally, the first acquired image sub-module or the second acquired image sub-module includes:
a receiving image unit configured to receive the biometric image of the target object uploaded by the user; or the like, or, alternatively,
the acquisition characteristic unit is configured to call an image acquisition component to acquire the biological characteristics of the target object based on an acquisition instruction submitted by the user to obtain the biological characteristic image; or the like, or, alternatively,
a scanning feature unit configured to obtain the biometric image by invoking the image acquisition component to scan the biometric.
Optionally, the target item includes: a pet insurance item, the biometric image, comprising: a nose print image, the identification model comprising: and (5) identifying a nose print.
To sum up, the present specification provides an identity recognition apparatus, which downloads an identity recognition model for a target object from a server according to a preset download address when a display page of the target item is monitored to be a preset page, so as to download the identity recognition model to a client when it is monitored that a user has an identification intention, perform identity recognition on an acquired biological feature image of the target object through the identity recognition model, obtain an identity recognition result of the target object, perform identity recognition on the target object at the client, reduce the recognition pressure of the server, provide the target item with identity recognition of the target object, and increase the security of the target item.
The above is a schematic scheme of an identification apparatus of this embodiment. It should be noted that the technical solution of the identity recognition apparatus and the technical solution of the identity recognition method belong to the same concept, and details that are not described in detail in the technical solution of the identity recognition apparatus can be referred to the description of the technical solution of the identity recognition method.
The present specification provides an embodiment of a computing device as follows:
FIG. 5 illustrates a block diagram of a computing device 500 provided in accordance with one embodiment of the present description. The components of the computing device 500 include, but are not limited to, a memory 510 and a processor 520. Processor 520 is coupled to memory 510 via bus 530, and database 550 is used to store data.
Computing device 500 also includes access device 540, access device 540 enabling computing device 500 to communicate via one or more networks 560. Examples of such networks include the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the internet. The access device 540 may include one or more of any type of network interface, e.g., a Network Interface Card (NIC), wired or wireless, such as an IEEE802.11 Wireless Local Area Network (WLAN) wireless interface, a worldwide interoperability for microwave access (Wi-MAX) interface, an ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a bluetooth interface, a Near Field Communication (NFC) interface, and so forth.
In one embodiment of the present description, the above-described components of computing device 500, as well as other components not shown in FIG. 5, may also be connected to each other, such as by a bus. It should be understood that the block diagram of the computing device architecture shown in FIG. 5 is for purposes of example only and is not limiting as to the scope of the present description. Those skilled in the art may add or replace other components as desired.
Computing device 500 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., tablet, personal digital assistant, laptop, notebook, netbook, etc.), mobile phone (e.g., smartphone), wearable computing device (e.g., smartwatch, smartglasses, etc.), or other type of mobile device, or a stationary computing device such as a desktop computer or PC. Computing device 500 may also be a mobile or stationary server.
Wherein processor 520 is configured to execute the following computer-executable instructions:
downloading an identity recognition model aiming at a target object from a server according to a preset downloading address under the condition that a display page of the target item is monitored to be a preset page; and performing identity recognition on the acquired biological characteristic image of the target object through the identity recognition model to obtain an identity recognition result of the target object.
The above is an illustrative scheme of a computing device of the present embodiment. It should be noted that the technical solution of the computing device and the technical solution of the above-mentioned identity recognition method belong to the same concept, and details that are not described in detail in the technical solution of the computing device can be referred to the description of the technical solution of the above-mentioned identity recognition method.
This specification provides one example of a computer-readable storage medium, comprising:
the present specification provides a computer readable storage medium storing computer instructions that, when executed by a processor, are operable to:
downloading an identity recognition model aiming at a target object from a server according to a preset downloading address under the condition that a display page of the target item is monitored to be a preset page; and performing identity recognition on the acquired biological characteristic image of the target object through the identity recognition model to obtain an identity recognition result of the target object.
The above is an illustrative scheme of a computer-readable storage medium of the present embodiment. It should be noted that the technical solution of the storage medium belongs to the same concept as the technical solution of the above-mentioned identification method, and details that are not described in detail in the technical solution of the storage medium can be referred to the description of the technical solution of the above-mentioned identification method.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The computer instructions comprise computer program code which may be in the form of source code, object code, an executable file or some intermediate form, or the like. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
It should be noted that, for the sake of simplicity, the foregoing method embodiments are described as a series of acts, but those skilled in the art should understand that the present embodiment is not limited by the described acts, because some steps may be performed in other sequences or simultaneously according to the present embodiment. Further, those skilled in the art should also appreciate that the embodiments described in this specification are preferred embodiments and that acts and modules referred to are not necessarily required for an embodiment of the specification.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
The preferred embodiments of the present specification disclosed above are intended only to aid in the description of the specification. Alternative embodiments are not exhaustive and do not limit the invention to the precise embodiments described. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the embodiments and the practical application, to thereby enable others skilled in the art to best understand and utilize the embodiments. The specification is limited only by the claims and their full scope and equivalents.
Claims (14)
1. An identity recognition method, comprising:
downloading an identity recognition model aiming at a target object from a server according to a preset downloading address under the condition that a display page of the target item is monitored to be a preset page;
and performing identity recognition on the acquired biological characteristic image of the target object through the identity recognition model to obtain an identity recognition result of the target object.
2. The identity recognition method according to claim 1, wherein downloading the identity recognition model for the target object from the server according to a preset download address when it is monitored that the display page of the target item is a preset page, comprises:
receiving a participation request submitted by a user aiming at the target project;
displaying an identity entry page for the target object based on the participation request;
under the condition that the identity input page is monitored to be the preset page, downloading an identity recognition model aiming at a target object from a server according to a preset downloading address, wherein the identity recognition model comprises: a first identity recognition model.
3. The identity recognition method according to claim 2, wherein the obtaining of the identity recognition result of the target object by performing identity recognition on the acquired biometric image of the target object through the identity recognition model comprises:
acquiring the biological characteristic image of the target object;
inputting the biological characteristic image into the first identity recognition model for identity recognition to obtain reference identity characteristic information of the target object;
and uploading the reference identity characteristic information and the biological characteristic image as the identity information of the target object to the server.
4. The identity recognition method according to claim 1, wherein downloading the identity recognition model for the target object from the server according to a preset download address when it is monitored that the display page of the target item is a preset page, comprises:
receiving a project processing request of a user for the target project;
displaying an identification page aiming at the target object based on the project processing request;
under the condition that the identification page is monitored to be the preset page, downloading an identification model aiming at a target object from a server according to a preset downloading address, wherein the identification model comprises: a first identity recognition model and a second identity recognition model.
5. The identity recognition method of claim 4, wherein the obtaining of the identity recognition result of the target object by performing identity recognition on the acquired biometric image of the target object through the identity recognition model comprises:
acquiring the biological characteristic image of the target object;
inputting the biological characteristic image into the first identity recognition model for identity recognition to obtain identity characteristic information of the target object;
acquiring reference identity characteristic information of the target object prestored in the server;
inputting the identity characteristic information and the reference identity characteristic information into the second identity recognition model for similarity calculation to obtain a similarity calculation result;
and determining that the identity recognition result of the target object is passed and displayed when the similarity calculation result is greater than a similarity threshold value.
6. The identity recognition method of claim 5, after obtaining the similarity calculation result, further comprising:
and under the condition that the similarity calculation result is less than or equal to the similarity threshold, determining that the identity recognition result of the target object is identity recognition failure and displaying the identity recognition result.
7. The identity recognition method according to claim 1, further comprising, after downloading the identity recognition model for the target object from the server according to the preset download address:
displaying a downloading progress aiming at the identity recognition model;
under the condition that the downloading time length of the identity recognition model is longer than the preset time length, acquiring the biological characteristic image of the target object;
and uploading the biological characteristic image to the server, and receiving an identity recognition result aiming at the target object sent by the server.
8. The identity recognition method according to claim 1, wherein when it is monitored that the display page of the target item is a preset page, the method further comprises:
under the condition that a display page of a target item is monitored to be a preset page, judging whether the identity recognition model exists in a storage space corresponding to the display page or not;
if so, performing identity recognition on the acquired biological characteristic image of the target object through the identity recognition model to obtain an identity recognition result of the target object;
and if not, downloading the identity recognition model aiming at the target object from the server according to the preset downloading address.
9. The identity recognition method according to claim 1, wherein when it is monitored that the display page of the target item is a preset page, the method further comprises:
determining version information of the identity recognition model;
under the condition that the storage space has the target identity recognition model, acquiring target version information of the target identity recognition model in the storage space;
judging whether the target version information is consistent with the version information of the identity recognition model or not;
if so, taking the target identity recognition model as the identity recognition model, and performing identity recognition on the acquired biological characteristic image of the target object through the identity recognition model to obtain an identity recognition result of the target object;
and if not, downloading the identity recognition model aiming at the target object from the server according to the preset downloading address.
10. The identification method of claim 3, 5 or 7, wherein the obtaining the biometric image of the target object comprises:
receiving the biometric image of the target object uploaded by the user; or the like, or, alternatively,
based on an acquisition instruction submitted by the user, calling an image acquisition component to acquire the biological characteristics of the target object to obtain a biological characteristic image; or the like, or, alternatively,
and acquiring the biological characteristic image by calling the image acquisition component to scan the biological characteristic.
11. The identification method of claim 1, the target item, comprising: pet insurance, the biometric image, comprising: a nose print image, the identification model comprising: and (5) identifying a nose print.
12. An identification device comprising:
the downloading module is configured to download the identity recognition model aiming at the target object from the server according to a preset downloading address under the condition that the display page of the target item is monitored to be a preset page;
and the identification module is configured to identify the acquired biological characteristic image of the target object through the identification model to obtain an identification result of the target object.
13. A computing device, comprising:
a memory and a processor;
the memory is configured to store computer-executable instructions, and the processor is configured to execute the computer-executable instructions to implement the method of:
downloading an identity recognition model aiming at a target object from a server according to a preset downloading address under the condition that a display page of the target item is monitored to be a preset page;
and performing identity recognition on the acquired biological characteristic image of the target object through the identity recognition model to obtain an identity recognition result of the target object.
14. A computer readable storage medium storing computer instructions which, when executed by a processor, carry out the steps of the identification method of any one of claims 1 to 11.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011193861.8A CN112231672A (en) | 2020-10-30 | 2020-10-30 | Identity recognition method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011193861.8A CN112231672A (en) | 2020-10-30 | 2020-10-30 | Identity recognition method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112231672A true CN112231672A (en) | 2021-01-15 |
Family
ID=74122651
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011193861.8A Pending CN112231672A (en) | 2020-10-30 | 2020-10-30 | Identity recognition method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112231672A (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109948458A (en) * | 2019-02-25 | 2019-06-28 | 广东智媒云图科技股份有限公司 | Pet personal identification method, device, equipment and storage medium based on noseprint |
| CN110245559A (en) * | 2019-05-09 | 2019-09-17 | 平安科技（深圳）有限公司 | Real-time object identification method, device and computer equipment |
| CN110704646A (en) * | 2019-10-16 | 2020-01-17 | 支付宝(杭州)信息技术有限公司 | Method and device for establishing stored material file |
| CN110909683A (en) * | 2019-11-25 | 2020-03-24 | 支付宝(杭州)信息技术有限公司 | Guarantee verification method and device based on guarantee project |
| CN110929650A (en) * | 2019-11-25 | 2020-03-27 | 支付宝(杭州)信息技术有限公司 | Method and device for identifying livestock and poultry |
-
2020
- 2020-10-30 CN CN202011193861.8A patent/CN112231672A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109948458A (en) * | 2019-02-25 | 2019-06-28 | 广东智媒云图科技股份有限公司 | Pet personal identification method, device, equipment and storage medium based on noseprint |
| CN110245559A (en) * | 2019-05-09 | 2019-09-17 | 平安科技（深圳）有限公司 | Real-time object identification method, device and computer equipment |
| CN110704646A (en) * | 2019-10-16 | 2020-01-17 | 支付宝(杭州)信息技术有限公司 | Method and device for establishing stored material file |
| CN110909683A (en) * | 2019-11-25 | 2020-03-24 | 支付宝(杭州)信息技术有限公司 | Guarantee verification method and device based on guarantee project |
| CN110929650A (en) * | 2019-11-25 | 2020-03-27 | 支付宝(杭州)信息技术有限公司 | Method and device for identifying livestock and poultry |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111144937B (en) | Advertisement material determining method, device, equipment and storage medium | |
| CN107229947B (en) | Animal identification-based financial insurance method and system | |
| CN110929650B (en) | Method and device for identifying livestock and feed identity, computing equipment and readable storage medium | |
| CN109255297B (en) | Animal state monitoring method, terminal device, storage medium and electronic device | |
| US9342735B2 (en) | Facial recognition lost pet identifying system | |
| CN112214748A (en) | Identity recognition system, method and device | |
| CN107680080B (en) | Sample library establishing method and checking method for livestock, storage medium and electronic equipment | |
| CN113011505B (en) | Thermodynamic diagram conversion model training method and device | |
| CN112035611B (en) | Target user recommendation method, device, computer equipment and storage medium | |
| CN110751621A (en) | Breast cancer auxiliary diagnosis method and device based on deep convolutional neural network | |
| CN110826371A (en) | Animal identification method, device, medium and electronic equipment | |
| CN109963072B (en) | Focusing method, focusing device, storage medium and electronic equipment | |
| CN114120090A (en) | Image processing method, device, equipment and storage medium | |
| CN112231672A (en) | Identity recognition method and device | |
| CN110909683B (en) | Guarantee verification method and device based on guarantee project | |
| CN110704646A (en) | Method and device for establishing stored material file | |
| CN111191066A (en) | Image recognition-based pet identity recognition method and device | |
| CN110765323A (en) | Community pet dog identification method, device, equipment and medium | |
| US11847849B2 (en) | System and method for companion animal identification based on artificial intelligence | |
| JP2022164589A (en) | Determination system | |
| CN111652746B (en) | Information generation method, device, electronic equipment and storage medium | |
| CN112132064A (en) | Method, device, equipment and medium for identifying number of pregnant sacs based on artificial intelligence | |
| CN111640491A (en) | System and method for self-service uploading and information management of medical detection documents | |
| CN113052074A (en) | Method, device, electronic equipment and medium for recording livestock feeding information | |
| JP7204852B1 (en) | Pet insurance assessment support device, pet insurance assessment support system, pet insurance assessment support method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| REG | Reference to a national code |
Ref country code: HK Ref legal event code: DE Ref document number: 40044753 Country of ref document: HK |
|
| TA01 | Transfer of patent application right |
Effective date of registration: 20211221 Address after: Room 610, floor 6, No. 618, Wai Road, Huangpu District, Shanghai 200010 Applicant after: Ant Shengxin (Shanghai) Information Technology Co.,Ltd. Address before: 801-11, Section B, 8th floor, 556 Xixi Road, Xihu District, Hangzhou City, Zhejiang Province, 310013 Applicant before: Alipay (Hangzhou) Information Technology Co.,Ltd. |
|
| TA01 | Transfer of patent application right | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210115 |
|
| RJ01 | Rejection of invention patent application after publication |