CN113915841A - Refrigerator and food material positioning method thereof - Google Patents
Refrigerator and food material positioning method thereof Download PDFInfo
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- CN113915841A CN113915841A CN202111212660.2A CN202111212660A CN113915841A CN 113915841 A CN113915841 A CN 113915841A CN 202111212660 A CN202111212660 A CN 202111212660A CN 113915841 A CN113915841 A CN 113915841A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
- F25D11/00—Self-contained movable devices, e.g. domestic refrigerators
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
- F25D29/00—Arrangement or mounting of control or safety devices
- F25D29/005—Mounting of control devices
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
- F25D2400/00—General features of, or devices for refrigerators, cold rooms, ice-boxes, or for cooling or freezing apparatus not covered by any other subclass
- F25D2400/36—Visual displays
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
- F25D2500/00—Problems to be solved
- F25D2500/06—Stock management
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Abstract
The invention discloses a refrigerator, comprising: a box body; the reader-writer comprises a reader-writer host and a plurality of antennas, and the reader-writer transmits or receives radio frequency signals to the RFID label through the antennas so that the RFID label calculates the signal intensity and returns the signal intensity to the reader-writer host through the antennas; the controller is configured to: when the preset positioning condition is met, acquiring the signal intensity and the food material information of the RFID label acquired by the reader-writer host; inputting the signal intensity of the RFID labels corresponding to the same food material information and received by different antennas into a pre-trained positioning model; the positioning model comprises a convolution layer, a pooling layer, an inclusion structure and a full-connection layer; acquiring positioning information output by the positioning model as the positioning information of the current food material; and displaying the positioning information of the current food material in the display. The invention discloses a food material positioning method of a refrigerator. By adopting the embodiment of the invention, the accuracy of positioning the food material can be improved, so that a user can quickly know the storage position of the food material.
Description
Technical Field
The invention relates to the technical field of refrigerators, in particular to a refrigerator and a food material positioning method thereof.
Background
The rapid development of the internet of things technology, the control technology and the communication technology promotes the intelligent high-speed development, and the household appliance industry has an intelligent trend and widely enters the families and lives of people. The method integrates the rapidness and convenience of the network into the design of the refrigerator product, provides more intelligent and humanized life experience for users, and gradually becomes an important development direction of the refrigerator product. The method comprises the steps that the food material positioning of the refrigerator is one of hot spot directions, an antenna is arranged at a specific position of the refrigerator, an RFID (Radio Frequency Identification) tag is placed on the food material in the refrigerator, data received by each tag are collected through a reader-writer, and then the data are processed through a corresponding classification algorithm to predict the position partition of each food material in the refrigerator, so that the intelligent management of the food material is realized. However, the existing technology for identifying the storage location of food based on RFID tag can only identify the storage room in which the food is stored, and cannot further identify the distribution location of the food in the storage room.
Disclosure of Invention
The embodiment of the invention aims to provide a refrigerator and a food material positioning method thereof, which can improve the accuracy of food material positioning and enable a user to quickly know the storage position of food material.
To achieve the above object, an embodiment of the present invention provides a refrigerator, including:
a cabinet serving as a support structure of the refrigerator and having a plurality of storage compartments therein;
the reader-writer is arranged in the box body and comprises a reader-writer host and a plurality of antennas, and the reader-writer transmits or receives radio frequency signals to the RFID label through the antennas so that the RFID label calculates the signal intensity and returns the signal intensity to the reader-writer host through the antennas;
the controller is configured to:
when a preset positioning condition is met, acquiring the signal intensity and the food material information of the RFID label acquired by the reader-writer host;
inputting the signal intensity of the RFID labels corresponding to the same food material information and received by different antennas into a pre-trained positioning model; the positioning model is obtained by pre-training a server and comprises a convolution layer, a pooling layer, an inclusion structure and a full-connection layer;
and acquiring the positioning information output by the positioning model as the positioning information of the current food material, and displaying the positioning information of the current food material in a display.
As an improvement of the above solution, the training method of the positioning model includes:
acquiring training data and preprocessing the training data; the training data comprises the signal intensity of the RFID labels to be trained, and the RFID labels to be trained are distributed in the storeroom according to a preset distribution rule;
building a positioning model;
inputting the training data into the positioning model for training.
As an improvement of the above scheme, the preprocessing the training data includes:
carrying out normalization processing on the training data;
and performing dimension increasing processing on the training data after the normalization processing so as to convert the training data into two-dimensional data.
As an improvement of the above scheme, the building positioning model includes:
padding with zero values at the edges of the input matrix;
after inputting the matrix, connecting a pan-convolution;
connecting two Incepotion structures after pan-convolution; wherein the inclusion structure is composed of a plurality of convolutions;
the inclusion structure is connected with the pooling layer;
and the full connecting layer is connected behind the pooling layer.
In order to achieve the above object, an embodiment of the present invention further provides a method for positioning food materials of a refrigerator, including:
when the preset positioning condition is met, acquiring the signal intensity and food material information of the RFID tag acquired by a reader-writer in the refrigerator; the reader-writer comprises a reader-writer host and a plurality of antennas, and the reader-writer transmits or receives radio frequency signals to the RFID label through the antennas so that the RFID label calculates the signal intensity and returns the signal intensity to the reader-writer host through the antennas;
inputting the signal intensity of the RFID labels corresponding to the same food material information and received by different antennas into a pre-trained positioning model; the positioning model is obtained by pre-training a server and comprises a convolution layer, a pooling layer, an inclusion structure and a full-connection layer;
and acquiring the positioning information output by the positioning model as the positioning information of the current food material, and displaying the positioning information of the current food material in a display.
As an improvement of the above solution, the training method of the positioning model includes:
acquiring training data and preprocessing the training data; the training data comprises the signal intensity of the RFID labels to be trained, and the RFID labels to be trained are distributed in the storeroom according to a preset distribution rule;
building a positioning model;
inputting the training data into the positioning model for training.
As an improvement of the above scheme, the preprocessing the training data includes:
carrying out normalization processing on the training data;
and performing dimension increasing processing on the training data after the normalization processing so as to convert the training data into two-dimensional data.
As an improvement of the above scheme, the building positioning model includes:
padding with zero values at the edges of the input matrix;
after inputting the matrix, connecting a pan-convolution;
connecting two Incepotion structures after pan-convolution; wherein the inclusion structure is composed of a plurality of convolutions;
the inclusion structure is connected with the pooling layer;
and the full connecting layer is connected behind the pooling layer.
Compared with the prior art, the refrigerator and the food material positioning method thereof disclosed by the embodiment of the invention have the advantages that the signal intensity of the RFID tag corresponding to the same food material information is identified through the storage positioning model in the refrigerator, so that the distribution position of the current food material in the storage chamber is identified, the positioning information is displayed in the display, and a user can conveniently and quickly know the storage position of the food material. The refrigerator provided by the embodiment of the invention can improve the accuracy of food material positioning, so that a user can quickly know the storage position of the food material.
Drawings
Fig. 1 is a schematic structural diagram of a refrigerator according to an embodiment of the present invention;
fig. 2 is a schematic distribution diagram of an antenna provided by an embodiment of the present invention in a refrigerator;
FIG. 3 is a block diagram of a positioning model provided by an embodiment of the present invention;
fig. 4 is a flowchart of a food material positioning method for a refrigerator according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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 invention.
Referring to fig. 1, a schematic structural diagram of a refrigerator provided in embodiment 1 of the present invention is shown, where the refrigerator includes:
a cabinet 10 serving as a support structure of the refrigerator and having a plurality of storage compartments therein;
the reader-writer 20 is arranged in the box body and comprises a reader-writer host and a plurality of antennas, and the reader-writer transmits or receives radio frequency signals to the RFID label through the antennas so that the RFID label calculates the signal intensity and returns the signal intensity to the reader-writer host through the antennas;
the controller 30 is configured to:
when a preset positioning condition is met, acquiring the signal intensity and the food material information of the RFID label acquired by the reader-writer host;
inputting the signal intensity of the RFID labels corresponding to the same food material information and received by different antennas into a pre-trained positioning model; the positioning model is obtained by pre-training a server and comprises a convolution layer, a pooling layer, an inclusion structure and a full-connection layer;
and acquiring the positioning information output by the positioning model as the positioning information of the current food material, and displaying the positioning information of the current food material in a display.
Specifically, referring to fig. 2, in the embodiment of the present invention, the refrigerator is divided into three partitions, each partition is distributed with antennas, and it should be noted that the dividing manner of the partitions of the refrigerator may be divided according to the distribution manner of the storage chambers, which is not limited herein. The positioning condition includes at least one of: acquiring a positioning instruction of a certain food material sent by a user; the method is triggered automatically after a preset positioning period, for example, the positioning period is 2 days.
Illustratively, in the embodiment of the invention, eight antennas are arranged inside the refrigerator, and the radio frequency identification technology is used for collecting the signal strength measured by each RFID tag. After the food and the RFID tags are bound and placed in the storage room by the user, the eight antennas simultaneously send signals, so that eight data are measured by each RFID tag, namely the signal intensity and the food information of the No. 1 to No. 8 antennas corresponding to the tag position, and the food information is used for distinguishing the signal intensity subsequently. The method comprises the steps that the RFID tags send out measured signal strength after receiving signals sent by antennas, a reader-writer host at the top of a refrigerator receives reading data in sequence, then the signal strength of the RFID tags corresponding to the same food material information and received by different antennas is input into a pre-trained positioning model, and therefore positioning information output by the positioning model is obtained and used as positioning information of current food materials, and the positioning information of the current food materials is displayed on a display.
Further, in the embodiment of the present invention, the display may display a three-dimensional model of a storage room of the refrigerator, and mark the positioning information of the current food material in the three-dimensional model, so that the user can know the position of the current food material according to the mark.
Optionally, the training method of the positioning model includes:
acquiring training data and preprocessing the training data; the training data comprises the signal intensity of the RFID labels to be trained, and the RFID labels to be trained are distributed in the storeroom according to a preset distribution rule;
building a positioning model;
inputting the training data into the positioning model for training.
Specifically, the distribution rule is: and distributing the RFID labels to be trained at equal intervals according to preset intervals. In the training process, the distribution space of the storage room needs to be divided into a plurality of areas at equal intervals, and an RFID label to be trained is placed in each area. It will be appreciated that the more zones divided, the smaller the spacing between the RFID tags to be trained, and the more accurate the positioning.
Before the training data are input into a positioning model, preprocessing needs to be carried out on the training data, firstly, normalization processing is carried out on the training data, the training data are mapped into an interval from 0 to 1, the convergence speed of a neural network model is improved, and the time needed by training is shortened; and then, performing dimension increasing processing on the training data after the normalization processing to convert the training data into two-dimensional data, expanding the two dimensions of the data, storing the extracted two-dimensional data in a csv file, regarding the data of each line in the csv file as a picture, regarding the line number of the file as the number of the pictures, representing the signal intensity in the form of the pictures, and facilitating the identification of a positioning model.
Specifically, the building and positioning model comprises the following steps: padding with zero values at the edges of the input matrix; after inputting the matrix, connecting a pan-convolution; connecting two Incepotion structures after pan-convolution; wherein the inclusion structure is composed of a plurality of convolutions; the inclusion structure is connected with the pooling layer; and the full connecting layer is connected behind the pooling layer.
Illustratively, referring to fig. 3, after data preprocessing, the training data is input into a feature matrix of 8 × 1 size, and zero values are filled in the edges of the input matrix to increase the height and width of the input feature matrix for facilitating subsequent convolution operations. The generalized convolution is followed by a 1 x 1 convolution in order to change the dimensionality of the data and increase the number of channels input to the feature matrix. After the operation of pan-convolution and 1 × 1 convolution, two rows of two columns of zero values are respectively filled in the upper, lower, left and right sides of the original feature matrix, and in the 1 × 1 convolution step, six convolution kernels participate in convolution operation, so that the size of the input feature matrix is changed into 12 × 5 × 6. And then connecting two addition blocks with the same structure, wherein each addition structure consists of four branches, the first branch only performs 1 × 1 convolution operation on the input feature matrix, the second branch performs 1 × 1 convolution on the input feature matrix, then performs convolution operation by using a convolution kernel with the size of 3 × 3, the third branch performs convolution processing by using a convolution kernel with the size of 5 × 5 after performing 1 × 1 convolution operation, and the last branch performs maximum pooling downsampling on the input feature matrix firstly and then performs 1 × 1 convolution operation. The width and the height of the feature matrix output by each branch are kept consistent in the whole process, and then all the output feature matrices are spliced together in the depth direction on a DepthCocato layer to obtain a complete output feature matrix. After the processing of the two layers of the inclusion structures, the size of the output feature matrix is 12 x 5 x 48, the global average pooling down-sampling is carried out behind the inclusion structure, the size of the output feature matrix is 6 x 2 x 48 after the sampling is finished, and finally the output feature matrix is in full connection with three output nodes to output a training result.
Compared with the prior art, the refrigerator disclosed by the embodiment of the invention has the advantages that the signal intensity of the RFID tag corresponding to the same food material information is identified through the storage positioning model in the refrigerator, so that the distribution position of the current food material in the storage chamber is identified, the positioning information is displayed in the display, and a user can conveniently and quickly know the storage position of the food material. The refrigerator provided by the embodiment of the invention can improve the accuracy of food material positioning, so that a user can quickly know the storage position of the food material.
Referring to fig. 4, fig. 4 is a flowchart of a food material positioning method for a refrigerator according to an embodiment of the present invention, where the food material positioning method for the refrigerator includes:
s1, when the preset positioning condition is met, acquiring the signal intensity and the food material information of the RFID label acquired by the reader-writer in the refrigerator; the reader-writer comprises a reader-writer host and a plurality of antennas, and the reader-writer transmits or receives radio frequency signals to the RFID label through the antennas so that the RFID label calculates the signal intensity and returns the signal intensity to the reader-writer host through the antennas;
s2, inputting the signal intensity of the RFID labels corresponding to the same food material information and received by different antennas into a pre-trained positioning model; the positioning model is obtained by pre-training a server and comprises a convolution layer, a pooling layer, an inclusion structure and a full-connection layer;
s3, acquiring the positioning information output by the positioning model as the positioning information of the current food material, and displaying the positioning information of the current food material on a display.
Specifically, in the embodiment of the present invention, the refrigerator is divided into three partitions, and each partition is distributed with antennas, and it should be noted that the dividing manner of the partitions of the refrigerator may be divided according to the distribution manner of the storage chambers, which is not specifically limited herein. The positioning condition includes at least one of: acquiring a positioning instruction of a certain food material sent by a user; the method is triggered automatically after a preset positioning period, for example, the positioning period is 2 days.
Illustratively, in the embodiment of the invention, eight antennas are arranged inside the refrigerator, and the radio frequency identification technology is used for collecting the signal strength measured by each RFID tag. After the food and the RFID tags are bound and placed in the storage room by the user, the eight antennas simultaneously send signals, so that eight data are measured by each RFID tag, namely the signal intensity and the food information of the No. 1 to No. 8 antennas corresponding to the tag position, and the food information is used for distinguishing the signal intensity subsequently. The method comprises the steps that the RFID tags send out measured signal strength after receiving signals sent by antennas, a reader-writer host at the top of a refrigerator receives reading data in sequence, then the signal strength of the RFID tags corresponding to the same food material information and received by different antennas is input into a pre-trained positioning model, and therefore positioning information output by the positioning model is obtained and used as positioning information of current food materials, and the positioning information of the current food materials is displayed on a display.
Further, in the embodiment of the present invention, the display may display a three-dimensional model of a storage room of the refrigerator, and mark the positioning information of the current food material in the three-dimensional model, so that the user can know the position of the current food material according to the mark.
Optionally, the training method of the positioning model includes steps S21 to S23:
s21, acquiring training data and preprocessing the training data; the training data comprises the signal intensity of the RFID labels to be trained, and the RFID labels to be trained are distributed in the storeroom according to a preset distribution rule;
s22, building a positioning model;
and S23, inputting the training data into the positioning model for training.
Specifically, the distribution rule is: and distributing the RFID labels to be trained at equal intervals according to preset intervals. In the training process, the distribution space of the storage room needs to be divided into a plurality of areas at equal intervals, and an RFID label to be trained is placed in each area. It will be appreciated that the more zones divided, the smaller the spacing between the RFID tags to be trained, and the more accurate the positioning.
Before the training data are input into a positioning model, preprocessing needs to be carried out on the training data, firstly, normalization processing is carried out on the training data, the training data are mapped into an interval from 0 to 1, the convergence speed of a neural network model is improved, and the time needed by training is shortened; and then, performing dimension increasing processing on the training data after the normalization processing to convert the training data into two-dimensional data, expanding the two dimensions of the data, storing the extracted two-dimensional data in a csv file, regarding the data of each line in the csv file as a picture, regarding the line number of the file as the number of the pictures, representing the signal intensity in the form of the pictures, and facilitating the identification of a positioning model.
Specifically, the building and positioning model comprises the following steps: padding with zero values at the edges of the input matrix; after inputting the matrix, connecting a pan-convolution; connecting two Incepotion structures after pan-convolution; wherein the inclusion structure is composed of a plurality of convolutions; the inclusion structure is connected with the pooling layer; and the full connecting layer is connected behind the pooling layer.
Illustratively, after data preprocessing, the training data is input into a feature matrix with a size of 8 × 1, and zero values are filled in the edges of the input matrix to increase the height and width of the input feature matrix for facilitating subsequent convolution operations. The generalized convolution is followed by a 1 x 1 convolution in order to change the dimensionality of the data and increase the number of channels input to the feature matrix. After the operation of pan-convolution and 1 × 1 convolution, two rows of two columns of zero values are respectively filled in the upper, lower, left and right sides of the original feature matrix, and in the 1 × 1 convolution step, six convolution kernels participate in convolution operation, so that the size of the input feature matrix is changed into 12 × 5 × 6. And then connecting two addition blocks with the same structure, wherein each addition structure consists of four branches, the first branch only performs 1 × 1 convolution operation on the input feature matrix, the second branch performs 1 × 1 convolution on the input feature matrix, then performs convolution operation by using a convolution kernel with the size of 3 × 3, the third branch performs convolution processing by using a convolution kernel with the size of 5 × 5 after performing 1 × 1 convolution operation, and the last branch performs maximum pooling downsampling on the input feature matrix firstly and then performs 1 × 1 convolution operation. The width and the height of the feature matrix output by each branch are kept consistent in the whole process, and then all the output feature matrices are spliced together in the depth direction on a DepthCocato layer to obtain a complete output feature matrix. After the processing of the two layers of the inclusion structures, the size of the output feature matrix is 12 x 5 x 48, the global average pooling down-sampling is carried out behind the inclusion structure, the size of the output feature matrix is 6 x 2 x 48 after the sampling is finished, and finally the output feature matrix is in full connection with three output nodes to output a training result.
Compared with the prior art, the food material positioning method of the refrigerator disclosed by the embodiment of the invention has the advantages that the signal intensity of the RFID tag corresponding to the same food material information is identified through the storage positioning model in the refrigerator, so that the distribution position of the current food material in the storage chamber is identified, the positioning information is displayed in the display, and a user can conveniently and quickly know the storage position of the food material. The refrigerator provided by the embodiment of the invention can improve the accuracy of food material positioning, so that a user can quickly know the storage position of the food material.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (8)
1. A refrigerator, characterized by comprising:
a cabinet serving as a support structure of the refrigerator and having a plurality of storage compartments therein;
the reader-writer is arranged in the box body and comprises a reader-writer host and a plurality of antennas, and the reader-writer transmits or receives radio frequency signals to the RFID label through the antennas so that the RFID label calculates the signal intensity and returns the signal intensity to the reader-writer host through the antennas;
the controller is configured to:
when a preset positioning condition is met, acquiring the signal intensity and the food material information of the RFID label acquired by the reader-writer host;
inputting the signal intensity of the RFID labels corresponding to the same food material information and received by different antennas into a pre-trained positioning model; the positioning model is obtained by pre-training a server and comprises a convolution layer, a pooling layer, an inclusion structure and a full-connection layer;
and acquiring the positioning information output by the positioning model as the positioning information of the current food material, and displaying the positioning information of the current food material in a display.
2. The refrigerator of claim 1, wherein the training method of the positioning model comprises:
acquiring training data and preprocessing the training data; the training data comprises the signal intensity of the RFID labels to be trained, and the RFID labels to be trained are distributed in the storeroom according to a preset distribution rule;
building a positioning model;
inputting the training data into the positioning model for training.
3. The refrigerator of claim 2, wherein the preprocessing the training data comprises:
carrying out normalization processing on the training data;
and performing dimension increasing processing on the training data after the normalization processing so as to convert the training data into two-dimensional data.
4. The refrigerator according to claim 2, wherein the building of the positioning model comprises:
padding with zero values at the edges of the input matrix;
after inputting the matrix, connecting a pan-convolution;
connecting two Incepotion structures after pan-convolution; wherein the inclusion structure is composed of a plurality of convolutions;
the inclusion structure is connected with the pooling layer;
and the full connecting layer is connected behind the pooling layer.
5. A food material positioning method of a refrigerator is characterized by comprising the following steps:
when the preset positioning condition is met, acquiring the signal intensity and food material information of the RFID tag acquired by a reader-writer in the refrigerator; the reader-writer comprises a reader-writer host and a plurality of antennas, and the reader-writer transmits or receives radio frequency signals to the RFID label through the antennas so that the RFID label calculates the signal intensity and returns the signal intensity to the reader-writer host through the antennas;
inputting the signal intensity of the RFID labels corresponding to the same food material information and received by different antennas into a pre-trained positioning model; the positioning model is obtained by pre-training a server and comprises a convolution layer, a pooling layer, an inclusion structure and a full-connection layer;
and acquiring the positioning information output by the positioning model as the positioning information of the current food material, and displaying the positioning information of the current food material in a display.
6. The food material positioning method for the refrigerator as claimed in claim 5, wherein the training method of the positioning model comprises:
acquiring training data and preprocessing the training data; the training data comprises the signal intensity of the RFID labels to be trained, and the RFID labels to be trained are distributed in the storeroom according to a preset distribution rule;
building a positioning model;
inputting the training data into the positioning model for training.
7. The food material positioning method for the refrigerator as claimed in claim 6, wherein the pre-processing of the training data comprises:
carrying out normalization processing on the training data;
and performing dimension increasing processing on the training data after the normalization processing so as to convert the training data into two-dimensional data.
8. The food material positioning method for the refrigerator as claimed in claim 6, wherein the building of the positioning model comprises:
padding with zero values at the edges of the input matrix;
after inputting the matrix, connecting a pan-convolution;
connecting two Incepotion structures after pan-convolution; wherein the inclusion structure is composed of a plurality of convolutions;
the inclusion structure is connected with the pooling layer;
and the full connecting layer is connected behind the pooling layer.
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| CN202111212660.2A CN113915841B (en) | 2021-10-18 | 2021-10-18 | Refrigerator and food material positioning method thereof |
| CN202280052817.6A CN117730235A (en) | 2021-10-18 | 2022-09-20 | Refrigerator, refrigerator management system and control method of refrigerator management system |
| PCT/CN2022/120029 WO2023065933A1 (en) | 2021-10-18 | 2022-09-20 | Refrigerator, refrigerator management system, and control method for refrigerator management system |
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| CN202111212660.2A CN113915841B (en) | 2021-10-18 | 2021-10-18 | Refrigerator and food material positioning method thereof |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114485037A (en) * | 2022-02-11 | 2022-05-13 | 海信（山东）冰箱有限公司 | Refrigerator and food material positioning method thereof |
| WO2023065933A1 (en) * | 2021-10-18 | 2023-04-27 | 海信冰箱有限公司 | Refrigerator, refrigerator management system, and control method for refrigerator management system |
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Address after: 266000 Haixin Avenue, Nancun Town, Pingdu City, Qingdao City, Shandong Province Applicant after: Hisense refrigerator Co.,Ltd. Address before: 266100 Songling Road, Laoshan District, Qingdao, Shandong Province, No. 399 Applicant before: HISENSE (SHANDONG) REFRIGERATOR Co.,Ltd. |
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