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Contact Wire Support Defect Detection Using Deep Bayesian Segmentation Neural Networks and Prior Geometric Knowledge.

, , , , , and . IEEE Access, (2019)

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Contact Wire Support Defect Detection Using Deep Bayesian Segmentation Neural Networks and Prior Geometric Knowledge., , , , , and . IEEE Access, (2019)A Robust Pantograph-Catenary Interaction Condition Monitoring Method Based on Deep Convolutional Network., , , , , and . IEEE Trans. Instrum. Meas., 69 (5): 1920-1929 (2020)Toward Reliable High-Speed Railway Pantograph-Catenary System State Detection: Multitask Deep Neural Networks With Runtime Reliability Monitoring., , , , , , and . IEEE Trans. Instrum. Meas., (2024)Real-Time Defect Detection of Track Components: Considering Class Imbalance and Subtle Difference Between Classes., , , and . IEEE Trans. Instrum. Meas., (2021)Adaptive Deep Learning for High-Speed Railway Catenary Swivel Clevis Defects Detection., , , , , and . IEEE Trans. Intell. Transp. Syst., 23 (2): 1299-1310 (2022)DefGAN: Defect Detection GANs With Latent Space Pitting for High-Speed Railway Insulator., , , , , and . IEEE Trans. Instrum. Meas., (2021)A Survey on Automatic Inspections of Overhead Contact Lines by Computer Vision., , , , , and . IEEE Trans. Intell. Transp. Syst., 23 (8): 10104-10125 (2022)Deep Architecture for High-Speed Railway Insulator Surface Defect Detection: Denoising Autoencoder With Multitask Learning., , , and . IEEE Trans. Instrum. Meas., 68 (8): 2679-2690 (2019)