A CNN-Based Defect Inspection Method for Catenary Split Pins in High-Speed Railway
A CNN-Based Defect Inspection Method for Catenary Split Pins in High-Speed Railway is a scholarly work, published in 2019 in ''IEEE Transactions on Instrumentation and Measurement''. The main subjects of the publication include pantograph, layer, convolutional neural network, deep learning, artificial intelligence, computer science, surface roughness, computer vision, Hough transform, discriminative model, artificial neural network, set, pattern recognition, -, catenary, and engineering. The authors present a three-stage automatic defect inspection system for SPs mainly based on an improved deep convolutional neural network (CNN), which is called PVANET++.