A Survey on Audio-Video Based Defect Detection Through Deep Learning in Railway Maintenance

A Survey on Audio-Video Based Defect Detection Through Deep Learning in Railway Maintenance

Within Artificial Intelligence, Deep Learning (DL) represents a paradigm that has been showing unprecedented performance in image and audio processing by supporting or even replacing humans in defect and anomaly detection. The railway sector is expected to benefit from DL applications, especially in...

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Bibliographic Details
Main Authors: Lorenzo De Donato, Francesco Flammini, Stefano Marrone, Claudio Mazzariello, Roberto Nardone, Carlo Sansone, Valeria Vittorini
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Computer vision
machine learning
fault detection
inspection
CNN
smart railways
Online Access:https://ieeexplore.ieee.org/document/9795283/

Internet

https://ieeexplore.ieee.org/document/9795283/

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