Dangerous working area accident automatic detection and alarm method based on deep learning
A deep learning and automatic detection technology, which is applied in neural learning methods, instruments, biological neural network models, etc., can solve the problems of detection, segmentation and labeling, detection models that are difficult to promote and monitor scenarios, etc.
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[0035]The following describes the implementation of the present invention in detail with reference to the drawings and embodiments.
[0036]Seefigure 1 , The present invention is based on the deep learning automatic detection and alarm method for workshop accidents, which monitors and alarms the surveillance video in real time, and can be used to detect accidents such as equipment collapse, equipment entrapment and equipment explosion. The scheme is as follows:
[0037]Obtain the original video data (video containing only normal scenes), extract the image from it and perform preprocessing, and convert the video into an acceptable input training set for the deep learning network.
[0038]Through the convolutional spatial autoencoder-decoder and convolutional temporal autoencoder-decoder, learn the feature patterns in the training video, and use the training set to train and optimize to obtain the workshop accident detection model. Anomaly detection is transformed into a spatiotemporal sequenc...
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