Intelligent Surveillance System Using Deep Learning
Keywords:
CNN, LSTM, RNN, Inception, GoogLeNet, VGG, AlexNet, Data-Set, Deep Learning, TensorFlowAbstract
It`s of intensive importance to develop a way for automatic surveillance video analysis to acknowledge the presence of violence. During this work, to identify violent videos, we recommend a deep neural network. A convolutional neural network is used with a pre-trained inception model for extracting frame level features from a video. The characteristics of the frame level are then collectively employed during a long remembering variant that uses fully connected layers and leaky rectified linear units. Alongside the long remembering, the convolutional neural network is capable of capturing localized spatio-temporal features that alter the analysis of native motion within the video. The performance is more evaluated in terms of accuracy of recognition on standard benchmark datasets. The approach planned outperforms state-of -the-art strategies whereas process the videos in real time.
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