Identity recognition method based on multi-channel space-time network and joint optimization loss

A spatiotemporal network and joint optimization technology, applied in the field of identity recognition, can solve the problems of complex calculation, long time consumption, and low accuracy of gait recognition across perspectives.

Pending Publication Date: 2020-12-25
ZHEJIANG NORMAL UNIVERSITY
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[0004] In order to solve some or some technical problems existing in the prior art, the present invention provides an identity recognition method based on multi-channel space-time network and joint optimization loss, which solves the problem of

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  • Identity recognition method based on multi-channel space-time network and joint optimization loss
  • Identity recognition method based on multi-channel space-time network and joint optimization loss
  • Identity recognition method based on multi-channel space-time network and joint optimization loss

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[0031] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. It should be noted that, on the premise of no conflict, the embodiments or technical features described below can be combined arbitrarily to form new embodiments. .

[0032] like Figures 1 to 3 As shown, an identification method based on a multi-channel spatiotemporal network and a joint optimization loss includes a multi-channel spatiotemporal network system and a joint optimization loss system, and the joint optimization loss system includes an improved ternary loss function, label smoothing regularization cross entropy The loss function has two parts, the label smoothing and regularization cross-entropy loss function is a cross-entropy loss function for the traditional classification network in the training process, and the label smoothing and regularization is integrated into the calculation of the cross-entropy loss. The steps of implementing...

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Abstract

The invention provides an identity recognition method based on a multi-channel space-time network and joint optimization loss, and the method employs a multi-channel space-time network system and a joint optimization loss system, and the joint optimization loss system comprises an improved ternary loss function and a label smooth regularization cross entropy loss function. The label smooth regularization cross entropy loss function is a cross entropy loss function for a traditional classification network in the training process, and label smooth regularization is fused into calculation of thecross entropy loss. The problems that gait recognition based on a traditional image method is low in cross-view accuracy, and a gait recognition method based on a model is complex in calculation, longin consumed time and the like are solved, and a method guarantee is provided for the real-time identity recognition technology.

Description

technical field [0001] The invention relates to the technical field of identification methods, in particular to an identification method based on a multi-channel spatiotemporal network and joint optimization loss. Background technique [0002] In recent years, artificial intelligence technology has become increasingly mature and gradually applied, and more and more industries have begun to enter the stage of intelligent technology innovation. The field of identity authentication has also gradually developed from the traditional user name / password authentication, IC card authentication, and dynamic password authentication to the existing human biometric authentication. Using the combination of computer technology and sensor technology to complete the identification of personal identity according to each person's unique physiological characteristics or behavioral characteristics is one of the most secure identity authentication technologies at present. As a new biometric iden...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V40/25G06N3/044G06N3/045G06F18/241G06F18/25G06F18/214
Inventor 蒋敏兰吴颖陈昊然
Owner ZHEJIANG NORMAL UNIVERSITY
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