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A Hyperautomative Human Behaviour Recognition Algorithm Based on Improved Residual Network by Jianxin Li; Jie Liu; Chao Li; Fei Jiang; Jinyu Huang; Shanshan Ji; Yang Liu is a Business, Management and Accounting article available to read on EtoBox.

What is A Hyperautomative Human Behaviour Recognition Algorithm Based on Improved Residual Network about?

ABSTRACT When dealing with the mutual storage relationship of behavioral features in long time sequence video, the convolutional neural network is easy to miss important feature information. To solve the above problems, this paper proposes a super automatic algorithm combining nonlocal convolution and three-dimensional convolution neural network. The algorithm uses sparse sampling to segment the long time sequence video to reduce the amount of redundant information, and integrates non-local convolution into the residual neural network, thus forming a super automatic full variational - L1 algorithm. Experimental results show that the proposed method can significantly improve the efficiency of behavior recognition.

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Author

Jianxin Li; Jie Liu; Chao Li; Fei Jiang; Jinyu Huang; Shanshan Ji; Yang Liu

Publisher

Informa UK Limited

Published

2023

Language

EN

Field

Business, Management and Accounting (Social Sciences)