Substation Foreign Object Intrusion Detection Method Based on Siamese Neural Network
In view of the existing inadequacies of conventional foreign object intrusion detection,this paper proposes a sub-station foreign object intrusion detection method based on siamese neural network.The siamese neural network is used to extract the moving foreground.The background image and the image to be detected are input to the siamese neural net-work at the same time,and the attention mechanism is introduced into the post-processing network.Finally the connected domain processing is used to directly output the foreign object detection results.This method has no limitation on the pre-set detection category of foreign objects.In addition,the designed data enhancement also further improves the anti-jitter and anti-illumination change ability of the algorithm.An accuracy rate of 98.35%and a recall rate of 98.61%achieved on the test data set prove the effectiveness of the model.
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