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- W3179390445 abstract "Abstract To solve the problem of inadequate expression of action behavior features, this paper proposes an action recognition method based on attention mechanism. Firstly, in the feature extraction part, a CSE module is designed to model action features spatio-temporally, and then this module is incorporated into the residual network to improve the feature extraction ability of the model; after that, the LSTM network is used to solve the problem of temporal association of features; finally, the actions are classified by Softmax. The experimental results show that the improved recognition rates of this method on UCF101, HMDB51 and Kinetics400 datasets are 96.23%, 92.03% and 75.65%, respectively." @default.
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- W3179390445 date "2021-07-01" @default.
- W3179390445 modified "2023-10-17" @default.
- W3179390445 title "A research of action recognition based on attention mechanism" @default.
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- W3179390445 doi "https://doi.org/10.1088/1742-6596/1966/1/012003" @default.
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