1. Institute of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China
2. Chinwangtao Technician College, Qinhuangdao, Hebei 066004, China
Abstract：In order to detect the smoking behavior in time and accurately judge the state. A smoking behavior detection algorithm based multi-task classification was proposed. The algorithm integrates multi-task convolution neural network, ensemble of regression trees cascade regression and depth residual network, quickly and accurately locates the region of interest through multi-task convolutional neural network algorithm and ERT cascade regression. Based on this, detect targets in the region of interest and identify status using deep residual network. The experimental results showed that the algorithm can accurately detect the occurrence of smoking behavior and make state judgments, the accuracy rate can reach 87.5%.
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2020, Vol. 41 
