Deep Learning algorithms represented by Convolutional Neural Networks can extract human behavior features more accurately and effectively,applying Deep Learning to human behavior recognition and prediction has become a research hotspot.On the basis of the classic HRnet network structure,this paper proposes a new network model L-HRnet by improving the L-Swish activation function and introducing the Squeeze-and-Excitation module,which is used to determine whether the behavioral actions of construction worker during high-altitude operations are dangerous.Behavioral classification and recognition experiments are conducted on the public dataset HMDB51,and the results show that the improved network structure L-HRnet had significantly better recognition accuracy than HRnet,effectively improving the protection level of high-altitude workers.
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