Intrusion detection for engineering vehicles under the transmission line based on deep learning
Chunjiang Yan, Chuang Wang, Juexiao Du, Hualin Fang, Yixuan Wang, Xuezhi Xiang, Xinli Guo · 2017
A two-step method based on deep learning is proposed for the intrusion detection of engineering vehicles working under high power transmission lines. In the first step, intrusion detection algorithm is used to identify the potential target area. Then the results are supplied to a trained deep convolution neural network classifier. This way combining intrusion detection method with CNN, the invasion of the engineering vehicles under high power transmission lines can efficiently be detected up to an accuracy of 97.2 %.