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Deep learning palm vein recognition system and method based on cloud side cooperative computing

A deep learning and recognition system technology, applied in the field of deep learning palm vein recognition system, can solve the problems of low recognition accuracy and slow response speed of the system, achieve rapid deployment and unified management, and improve the accuracy rate

Active Publication Date: 2019-11-05
WUHAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In view of this, the present invention provides a deep learning palm vein recognition system and method based on cloud-edge-end collaborative computing to solve or at least partially solve the problems of low system recognition accuracy and slow response speed in the prior art

Method used

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  • Deep learning palm vein recognition system and method based on cloud side cooperative computing
  • Deep learning palm vein recognition system and method based on cloud side cooperative computing
  • Deep learning palm vein recognition system and method based on cloud side cooperative computing

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Embodiment 1

[0053] This embodiment provides a deep learning palm vein recognition system based on cloud-side collaborative computing, which includes:

[0054] The cloud storage module is used to deploy the deep learning palm vein recognition algorithm, train the deep convolutional neural network model to obtain the deep learning palm vein recognition model, and store user information;

[0055] Palm vein collection and recognition equipment, including collection module, edge computing module, and receiving module. The collection module is used to collect the palm vein image of the user, and the edge computing module is used to call the deep learning palm vein recognition model to verify the collected palm vein image. If the verification is successful, upload the verification information to the cloud storage module. If the verification fails, receive the information input by the user through the receiving module, and match the information input by the user with the user information stored in the ...

Embodiment 2

[0067] This embodiment provides a deep learning palm vein recognition method based on cloud-side collaborative computing. Please refer to figure 2 , The method includes:

[0068] Step S1: Deploy the deep learning palm vein recognition algorithm through the cloud storage module, train the deep convolutional neural network model to obtain the deep learning palm vein recognition model, and store user information;

[0069] Step S2: Collect the palm vein image of the user through the acquisition module, and use the edge computing module to call the deep learning palm vein recognition model to verify the acquired palm vein image. When the verification is successful, the verification information is uploaded to the cloud storage module, and the verification fails. At the time, the information input by the user is received through the receiving module, and the information input by the user is matched with the user information stored in the cloud storage module to determine whether it is a n...

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Abstract

The invention discloses a deep learning palm vein recognition system based on cloud side cooperative computing. The system is mainly composed of a cloud computing layer, an edge computing layer and aterminal layer. The calculation and storage capabilities of the whole identification system are determined through the combination of three layers; the system specifically comprises a cloud storage module, palm vein acquisition and identification equipment and a client; the cloud storage module can provide computing resources required by training for the model and transmits the trained model to anedge calculation module of the palm vein acquisition equipment; the terminal collects the recognition condition of the deep convolutional neural network model, and feeds back the recognition condition to the deep convolutional neural network model chip on the cloud storage module through the edge calculation module.Continuous training, application, feedback and retraining are performed, and the accuracy of the finally obtained palm vein recognition model is greatly improved through repeated effective iterative training. The rear-end cloud storage module can also realize rapid deployment and unified management of the palm vein recognition system according to the resource configuration and management capability of the cloud platform.

Description

Technical field [0001] The invention relates to the technical field of pattern recognition, in particular to a deep learning palm vein recognition system and method based on cloud edge-end collaborative computing. Background technique [0002] In recent years, with the advent of the "intelligence age", AI technology has been increasingly applied to the field of biometric identification, which has greatly improved the safety, convenience, and accuracy of biometric technology. Palm vein recognition, as the world's only "second-generation biometric recognition technology", has unique advantages in anti-counterfeiting, accuracy and anti-interference. [0003] The full name of CNN is Convolutional Neural Networks, which is interpreted as Convolutional Neural Network in Chinese. It is a deep feedforward neural network with the characteristics of local connection, weight sharing and convergence. As a branch of deep neural networks, CNN has good applications in computer vision, natural la...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62
CPCG06V40/10G06V40/14G06V10/95G06V10/44G06F18/214
Inventor 赵俭辉周智袁志勇
Owner WUHAN UNIV
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