Video Surveillance Recognition Method Based on Convolutional Neural Network
Based on the overall structure of video surveillance system,this paper proposes a video surveillance recognition method based on convolutional neural network by introducing L2 regularization,to solve the problem of traditional systems in object recognition and anomaly detection.In addition,the proposed method is tested with UCF-Crime data set,the results show that the proposed method can successfully detect abnormal areas in different monitoring scenarios,and has good practical application potential.
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