Train rolling stock video segmentation and classification for bogie part inspection automation: a deep learning approach

Train rolling stock video segmentation and classification for bogie part inspection automation: a deep learning approach

Abstract Train rolling stock examination (TRSE) is a physical procedure for inspecting the bogie parts during transit at a little over 30 kmph. Currently, this process is manually performed across many railway networks across the world. This work proposes to automate the process of TRSE using artifi...

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Bibliographic Details
Main Authors: Kaja Krishnamohan, Ch. Raghava Prasad, P. V. V. Kishore
Format: Article
Language:English
Published: SpringerOpen 2022-08-01
Series:Journal of Engineering and Applied Science
Subjects:
Deep learning
Train rolling stock
Automation
Convolutional neural networks
UNet
Online Access:https://doi.org/10.1186/s44147-022-00128-x

Internet

https://doi.org/10.1186/s44147-022-00128-x

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