CN112037025A - Unmanned aerial vehicle-based bank potential public customer identification method, device and equipment - Google Patents

Unmanned aerial vehicle-based bank potential public customer identification method, device and equipment Download PDF

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Publication number
CN112037025A
CN112037025A CN202010903866.9A CN202010903866A CN112037025A CN 112037025 A CN112037025 A CN 112037025A CN 202010903866 A CN202010903866 A CN 202010903866A CN 112037025 A CN112037025 A CN 112037025A
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picture
building
bank
information
unmanned aerial
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CN112037025B (en
Inventor
黄文强
季蕴青
胡路苹
胡玮
黄雅楠
胡传杰
浮晨琪
李蚌蚌
申亚坤
徐晨敏
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Bank of China Ltd
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Bank of China Ltd
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    • 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
    • G06Q40/02—Banking, e.g. interest calculation or account maintenance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/084—Backpropagation, e.g. using gradient descent
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/086—Learning methods using evolutionary algorithms, e.g. genetic algorithms or genetic programming
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G06V20/176—Urban or other man-made structures
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/10—Internal combustion engine [ICE] based vehicles
    • Y02T10/40—Engine management systems

Abstract

The application discloses identification method, device and equipment of potential bank to public customers based on unmanned aerial vehicle, which can accurately identify potential companies by using the unmanned aerial vehicle and a pre-constructed neural network model, and meanwhile, the identified company name information is integrated to provide materials for bank staff, so that the bank staff can conveniently check and carry out targeted marketing. The method comprises the following steps: firstly, shooting a picture of a preset street position by using an unmanned aerial vehicle, sending the picture to a bank background system, then extracting picture characteristics of the picture, inputting the picture characteristics into a pre-constructed picture recognition model, judging whether a building in the picture is a company, if so, extracting company name information of the building in the picture, and providing the company name information for a bank worker.

Description

Unmanned aerial vehicle-based bank potential public customer identification method, device and equipment
Technical Field
The application relates to the technical field of computers, in particular to a bank potential public customer identification method, device and equipment based on an unmanned aerial vehicle.
Background
With the rapid development of scientific technology, China has entered the era of unmanned aerial vehicles, and because unmanned aerial vehicles have the advantages of low cost, economical use, strong effectiveness, high attendance rate and the like, the unmanned aerial vehicles are widely applied in a plurality of industries, so that more and more unmanned aerial vehicles appear at the sides of people.
At present, a large part of income of each bank is provided by the bank to public clients (namely, company clients), so that the company clients are popular with the bank, and the banks of some small companies are expected to be developed as customers in the era of national marketing of bank employees, but many banks do not know which positions in a city are distributed with the small companies and address information of the companies, so that it is difficult to accurately identify the potential marketing to the public clients.
Disclosure of Invention
The main purpose of the embodiment of the application is to provide a bank potential public client identification method, device and equipment based on an unmanned aerial vehicle, which can accurately identify potential companies by using the unmanned aerial vehicle and a pre-constructed neural network model, and meanwhile, the identified company name information is integrated to provide materials for bank staff, so that the bank staff can conveniently check and perform targeted marketing.
In a first aspect, an embodiment of the present application provides a method for identifying potential public customers of a bank based on an unmanned aerial vehicle, including:
shooting a picture of the position of a preset street by using an unmanned aerial vehicle, and sending the picture to a bank background system;
extracting picture characteristics of the picture, inputting the picture characteristics into a picture identification model which is constructed in advance, and judging whether a building in the picture is a company or not;
if yes, extracting the company name information of the building in the picture, and providing the company name information of the building to the staff of the bank.
Optionally, after the picture of the position of the preset street is taken by using the unmanned aerial vehicle, the method further includes:
acquiring the position information of the unmanned aerial vehicle;
identifying the distance and angle between the unmanned aerial vehicle and the building in the picture by using an infrared sensor;
and determining the position information of the building in the picture according to the position information of the unmanned aerial vehicle, the distance and the angle, and sending the position information of the building to the bank background system.
Optionally, the extracting the name information of the company in the picture and providing the name information to the staff of the bank includes:
extracting company name information of the building in the picture, and binding the company name information and the position information of the building to obtain first binding information;
binding the picture information of the picture with the company name information of the building to obtain second binding information;
and linking the detailed data information corresponding to the first binding information and the second binding information to a map, and providing the map for the staff of the bank to check.
Optionally, the image recognition model is a BP neural network model optimized by using a genetic algorithm.
In a second aspect, an embodiment of the present application further provides an identification apparatus for a potential bank to a public customer based on an unmanned aerial vehicle, including:
the system comprises a shooting unit, a bank background system and a control unit, wherein the shooting unit is used for shooting a picture of the position of a preset street by using an unmanned aerial vehicle and sending the picture to the bank background system;
the first extraction unit is used for extracting picture characteristics of the picture, inputting the picture characteristics into a picture identification model which is constructed in advance, and judging whether a building in the picture is a company or not;
and the second extraction unit is used for extracting the company name information of the building in the picture and providing the company name information to the staff of the bank if the building in the picture is judged to be a company.
Optionally, the apparatus further comprises:
the acquisition unit is used for acquiring the position information of the unmanned aerial vehicle;
the identification unit is used for identifying the distance and the angle between the unmanned aerial vehicle and the building in the picture by using an infrared sensor;
and the determining unit is used for determining the position information of the building in the picture according to the position information of the unmanned aerial vehicle, the distance and the angle, and sending the position information of the building to the bank background system.
Optionally, the second extracting unit includes:
the first binding subunit is used for extracting the company name information of the building in the picture and binding the company name information with the position information of the building to obtain first binding information;
the second binding subunit is used for binding the picture information of the picture with the company name information of the building to obtain second binding information;
and the link subunit is used for linking the detailed data information corresponding to the first binding information and the second binding information to a map and providing the map for the staff of the bank to check.
Optionally, the image recognition model is a BP neural network model optimized by using a genetic algorithm.
The embodiment of the application also provides a potential identification equipment to public customer of bank based on unmanned aerial vehicle, includes: a processor, a memory, a system bus;
the processor and the memory are connected through the system bus;
the memory is configured to store one or more programs, the one or more programs including instructions, which when executed by the processor, cause the processor to perform any one of the implementations of the drone-based bank potential public customer identification method described above.
The embodiment of the application also provides a computer-readable storage medium, wherein instructions are stored in the computer-readable storage medium, and when the instructions are run on the terminal device, the terminal device is enabled to execute any implementation manner of the unmanned aerial vehicle-based bank potential public customer identification method.
According to the method, the device and the equipment for identifying the potential public clients of the bank based on the unmanned aerial vehicle, firstly, the unmanned aerial vehicle is used for shooting a picture of the position of a preset street, the picture is sent to a bank background system, then, picture characteristics of the picture are extracted and input into a picture identification model which is constructed in advance, whether a building in the picture is a company or not is judged, if yes, company name information of the building in the picture is extracted, and the company name information is provided for a bank worker. Therefore, the potential companies can be accurately identified by using the unmanned aerial vehicle and the pre-constructed neural network model, and meanwhile, the identified company name information is integrated to provide materials for bank workers, so that the bank workers can conveniently check and carry out targeted marketing.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flowchart of a method for identifying potential public customers of a bank based on an unmanned aerial vehicle according to an embodiment of the present application;
fig. 2 is a schematic composition diagram of an identification apparatus for a potential public customer of a bank based on an unmanned aerial vehicle according to an embodiment of the present application.
Detailed Description
At present, a large part of income of each bank is provided by the bank to public clients (namely, company clients), so that the company clients are popular with the bank, and the bank is wanted to be cultivated as a client for some small company banks in the era of national marketing of the bank staff, but many banks do not know which positions in the city are distributed with the small companies and address information of the companies, so that how to accurately identify the potential marketing to the public clients is difficult.
In order to solve the above defects, an embodiment of the present application provides a method for identifying potential public customers of a bank based on an unmanned aerial vehicle, which includes steps of firstly, taking a picture of a preset street position by using the unmanned aerial vehicle, sending the picture to a bank background system, then, extracting picture features of the picture, inputting the picture features into a picture identification model constructed in advance, judging whether a building in the picture is a company, if so, extracting company name information of the building in the picture, and providing the company name information to a bank worker. Therefore, the potential companies can be accurately identified by using the unmanned aerial vehicle and the pre-constructed neural network model, and meanwhile, the identified company name information is integrated to provide materials for bank workers, so that the bank workers can conveniently check and carry out targeted marketing.
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
First embodiment
Referring to fig. 1, a schematic flow chart of a method for identifying potential public customers of a bank based on an unmanned aerial vehicle according to the present embodiment is provided, where the method includes the following steps:
s101: and shooting a picture of the position of the preset street by using the unmanned aerial vehicle, and sending the picture to a bank background system.
In this embodiment, in order to accurately identify potential public customers existing in the preset area for marketing, for a bank, the unmanned aerial vehicle is first required to take a picture of a position of a preset street, and send the picture to a bank background system for executing the subsequent step S102. For example, the unmanned aerial vehicle can be used to shoot pictures of positions of 5 streets with concentrated population in the region of the bank, and the pictures are stored on the unmanned aerial vehicle and then returned to the bank background system through the wireless network.
S102: and extracting picture characteristics of the picture, inputting the picture characteristics into a picture identification model which is constructed in advance, and judging whether the building in the picture is a company or not.
In this embodiment, after the picture of the position of the preset street is taken in step S101, the construction features (such as the outline shape) of the building in the picture can be further identified as the picture features, and the picture features are input into the pre-constructed picture recognition model to determine whether the building is a company.
In an alternative implementation manner, the picture recognition model refers to a BP neural network model optimized by using a genetic algorithm.
Specifically, the construction process of the picture identification model comprises the following steps: firstly, collecting a large number of pictures shot by an unmanned aerial vehicle, and manually marking out buildings serving as companies in the pictures as label data; then, the pictures shot by the unmanned aerial vehicle are used as input of the BP neural network model, the probability that the buildings in the pictures are companies is used as output, the BP neural network model is trained, meanwhile, a Genetic Algorithm (GA for short) is introduced in the training process to optimize the weight and the threshold of the model, and therefore the GA-BP neural network model is constructed. The BP neural network structure can be determined according to the number of network input and output, and the number of parameters needing to be optimized in the genetic algorithm is further determined. According to the kolmogorov principle, a three-layer BP neural network is enough to complete any mapping from n dimension to m dimension, generally only one hidden layer is needed, the number of hidden layer nodes is determined by a trial and error method, and therefore the optimal individual output by a genetic algorithm is used as the initial weight and the threshold of the BP neural network to train and learn the BP neural network, and the final GA-BP neural network structure is determined. And then, the GA-BP neural network model is tested by utilizing the test set in the previous label data, so that a picture identification model with higher accuracy is obtained.
It should be noted that, in a possible implementation manner of this embodiment, after the picture of the position of the preset street is taken by using the unmanned aerial vehicle in step 101, in order to accurately determine the position information of the company (i.e., the building in the drawing) existing in the area corresponding to the picture, the following steps a1-A3 are further performed:
step A1: acquiring position information of the unmanned aerial vehicle;
step A2: identifying the distance and the angle between the unmanned aerial vehicle and the building in the picture by using an infrared sensor;
step A3: and determining the position information of the building in the picture according to the position information of the unmanned aerial vehicle, the distance and the angle between the unmanned aerial vehicle and the building in the picture, and sending the position information of the building to a bank background system.
In this implementation, in order to accurately identify potential companies in the area corresponding to the picture, the position information of the current unmanned aerial vehicle may be detected by a Global Positioning System (GPS), then, the distance and angle between the unmanned aerial vehicle and the companies (i.e., buildings in the picture) existing in the area corresponding to the picture are identified by using an infrared sensor disposed on the unmanned aerial vehicle, then, the position information of the buildings in the picture may be calculated by using the distance and angle between the unmanned aerial vehicle and the companies (i.e., buildings in the picture) existing in the area corresponding to the picture and the position information of the unmanned aerial vehicle itself, and further, the position information of the buildings in the picture and the picture information may be bound and then stored on the unmanned aerial vehicle and transmitted to a bank background System, for example, when the unmanned aerial vehicle returns, the position information of the buildings and the picture information stored in the unmanned aerial vehicle may be transmitted to the bank background System by using a connection device, to perform the subsequent steps S102-S103.
S103: and if the buildings in the picture are judged to be companies, extracting company name information of the buildings in the picture, and providing the company name information to the staff of the bank.
In this embodiment, if it is determined that the building in the picture is a company through step S102, the company name information of the building in the picture can be further advanced by using the existing or future picture information advance method, and can be provided to the bank staff.
In a possible implementation manner of this embodiment, the specific implementation process of this step S103 may include the following steps B1-B3:
step B1: and extracting the company name information of the building in the picture, and binding the company name information and the position information of the building to obtain first binding information.
Step B2: and binding the picture information of the picture with the company name information of the building to obtain second binding information.
Step B3: and linking the detailed data information corresponding to the first binding information and the second binding information to a map, and providing the map for the staff of the bank to check.
In the implementation mode, if the building in the picture is judged to be a company through the picture identification model, the company name information of the building in the picture can be further extracted through the image identification model, the company name information and the position information of the building are bound, the first binding information is obtained, meanwhile, the picture information of the picture and the company name of the building can be bound, the second binding information is obtained, further, the detailed data information corresponding to the first binding information and the second binding information can be linked to a map to be provided for the staff of the bank to check, namely, the staff of the bank can screen potential public clients capable of carrying out marketing by inquiring the company information connected in the map, and a targeted marketing scheme is formulated, so that the purpose of precise marketing is achieved, and the efficiency of the staff of the bank is further improved, the cost of marketing to public customers by banks is reduced.
In summary, according to the identification method for potential public customers of the bank based on the unmanned aerial vehicle provided by this embodiment, firstly, the unmanned aerial vehicle is used to shoot a picture of a preset street, and the picture is sent to the bank background system, then, picture features of the picture are extracted and input to a picture identification model which is constructed in advance, whether a building in the picture is a company or not is judged, and if yes, company name information of the building in the picture is extracted and provided to a bank worker. Therefore, the potential companies can be accurately identified by using the unmanned aerial vehicle and the pre-constructed neural network model, and meanwhile, the identified company name information is integrated to provide materials for bank workers, so that the bank workers can conveniently check and carry out targeted marketing.
Second embodiment
In this embodiment, a device for identifying potential public customers of a bank based on an unmanned aerial vehicle will be described, and for related contents, please refer to the above method embodiment.
Referring to fig. 2, a schematic composition diagram of an identification apparatus for a potential public customer of a bank based on an unmanned aerial vehicle provided for this embodiment is provided, where the apparatus includes:
the shooting unit 201 is used for shooting a picture of a position where a preset street is located by using an unmanned aerial vehicle and sending the picture to a bank background system;
the first extraction unit 202 is configured to extract picture features of the picture, input the picture features into a picture identification model which is constructed in advance, and determine whether a building in the picture is a company;
and the second extraction unit 203 is used for extracting the company name information of the building in the picture and providing the company name information to the staff of the bank if the building in the picture is judged to be a company.
In an implementation manner of this embodiment, the apparatus further includes:
the acquisition unit is used for acquiring the position information of the unmanned aerial vehicle;
the identification unit is used for identifying the distance and the angle between the unmanned aerial vehicle and the building in the picture by using an infrared sensor;
and the determining unit is used for determining the position information of the building in the picture according to the position information of the unmanned aerial vehicle, the distance and the angle, and sending the position information of the building to the bank background system.
In an implementation manner of this embodiment, the second extraction unit 203 includes:
the first binding subunit is used for extracting the company name information of the building in the picture and binding the company name information with the position information of the building to obtain first binding information;
the second binding subunit is used for binding the picture information of the picture with the company name information of the building to obtain second binding information;
and the link subunit is used for linking the detailed data information corresponding to the first binding information and the second binding information to a map and providing the map for the staff of the bank to check.
In an implementation manner of this embodiment, the image recognition model is a BP neural network model optimized by using a genetic algorithm.
In summary, according to the identification apparatus for potential public customers of a bank based on an unmanned aerial vehicle provided by this embodiment, firstly, the unmanned aerial vehicle is used to shoot a picture of a preset street, and the picture is sent to a bank background system, then, picture features of the picture are extracted and input to a picture identification model which is constructed in advance, whether a building in the picture is a company or not is judged, and if yes, company name information of the building in the picture is extracted and provided to a bank worker. Therefore, the potential companies can be accurately identified by using the unmanned aerial vehicle and the pre-constructed neural network model, and meanwhile, the identified company name information is integrated to provide materials for bank workers, so that the bank workers can conveniently check and carry out targeted marketing.
Further, this application embodiment still provides a bank potential is to public customer's identification equipment based on unmanned aerial vehicle, includes: a processor, a memory, a system bus;
the processor and the memory are connected through the system bus;
the memory is for storing one or more programs, the one or more programs including instructions, which when executed by the processor, cause the processor to perform any of the above-described methods of drone-based bank potential identification of a public customer.
Further, an embodiment of the present application further provides a computer-readable storage medium, where instructions are stored in the computer-readable storage medium, and when the instructions are run on a terminal device, the terminal device is caused to execute any implementation method of the above method for identifying potential public customers by a bank based on an unmanned aerial vehicle.
As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that all or part of the steps in the above embodiment methods can be implemented by software plus a necessary general hardware platform. Based on such understanding, the technical solution of the present application may be essentially or partially implemented in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network communication device such as a media gateway, etc.) to execute the method according to the embodiments or some parts of the embodiments of the present application.
It should be noted that, in the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments may be referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
It is further noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. A bank potential public customer identification method based on an unmanned aerial vehicle is characterized by comprising the following steps:
shooting a picture of the position of a preset street by using an unmanned aerial vehicle, and sending the picture to a bank background system;
extracting picture characteristics of the picture, inputting the picture characteristics into a picture identification model which is constructed in advance, and judging whether a building in the picture is a company or not;
if yes, extracting the company name information of the building in the picture, and providing the company name information of the building to the staff of the bank.
2. The method of claim 1, wherein after the taking of the picture of the location of the preset street by the drone, the method further comprises:
acquiring the position information of the unmanned aerial vehicle;
identifying the distance and angle between the unmanned aerial vehicle and the building in the picture by using an infrared sensor;
and determining the position information of the building in the picture according to the position information of the unmanned aerial vehicle, the distance and the angle, and sending the position information of the building to the bank background system.
3. The method of claim 2, wherein said extracting and providing name information of said company in said picture to said bank staff comprises:
extracting company name information of the building in the picture, and binding the company name information and the position information of the building to obtain first binding information;
binding the picture information of the picture with the company name information of the building to obtain second binding information;
and linking the detailed data information corresponding to the first binding information and the second binding information to a map, and providing the map for the staff of the bank to check.
4. The method according to any one of claims 1 to 3, wherein the picture recognition model is a BP neural network model optimized by a genetic algorithm.
5. An unmanned aerial vehicle-based bank potential public customer identification device, comprising:
the system comprises a shooting unit, a bank background system and a control unit, wherein the shooting unit is used for shooting a picture of the position of a preset street by using an unmanned aerial vehicle and sending the picture to the bank background system;
the first extraction unit is used for extracting picture characteristics of the picture, inputting the picture characteristics into a picture identification model which is constructed in advance, and judging whether a building in the picture is a company or not;
and the second extraction unit is used for extracting the company name information of the building in the picture and providing the company name information to the staff of the bank if the building in the picture is judged to be a company.
6. The apparatus of claim 5, further comprising:
the acquisition unit is used for acquiring the position information of the unmanned aerial vehicle;
the identification unit is used for identifying the distance and the angle between the unmanned aerial vehicle and the building in the picture by using an infrared sensor;
and the determining unit is used for determining the position information of the building in the picture according to the position information of the unmanned aerial vehicle, the distance and the angle, and sending the position information of the building to the bank background system.
7. The apparatus of claim 6, wherein the second extraction unit comprises:
the first binding subunit is used for extracting the company name information of the building in the picture and binding the company name information with the position information of the building to obtain first binding information;
the second binding subunit is used for binding the picture information of the picture with the company name information of the building to obtain second binding information;
and the link subunit is used for linking the detailed data information corresponding to the first binding information and the second binding information to a map and providing the map for the staff of the bank to check.
8. The apparatus according to any one of claims 5 to 7, wherein the picture recognition model is a BP neural network model optimized by a genetic algorithm.
9. An unmanned aerial vehicle-based bank potential public customer identification device, comprising: a processor, a memory, a system bus;
the processor and the memory are connected through the system bus;
the memory is to store one or more programs, the one or more programs comprising instructions, which when executed by the processor, cause the processor to perform the method of any of claims 1-4.
10. A computer-readable storage medium having stored therein instructions that, when executed on a terminal device, cause the terminal device to perform the method of any one of claims 1-4.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103678305A (en) * 2012-08-31 2014-03-26 北京网秦天下科技有限公司 Method and system for displaying inquiring information based on image recognition
WO2020056677A1 (en) * 2018-09-20 2020-03-26 中建科技有限公司深圳分公司 Violation detection method, system, and device for building construction site
CN111507296A (en) * 2020-04-23 2020-08-07 嘉兴河图遥感技术有限公司 Intelligent illegal building extraction method based on unmanned aerial vehicle remote sensing and deep learning

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103678305A (en) * 2012-08-31 2014-03-26 北京网秦天下科技有限公司 Method and system for displaying inquiring information based on image recognition
WO2020056677A1 (en) * 2018-09-20 2020-03-26 中建科技有限公司深圳分公司 Violation detection method, system, and device for building construction site
CN111507296A (en) * 2020-04-23 2020-08-07 嘉兴河图遥感技术有限公司 Intelligent illegal building extraction method based on unmanned aerial vehicle remote sensing and deep learning

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