Railway Track Inspection Using Deep Learning Based on Audio to Spectrogram Conversion: An on-the-Fly Approach

The periodic inspection of railroad tracks is very important to find structural and geometrical problems that lead to railway accidents. Currently, in Pakistan, rail tracks are inspected by an acoustic-based manual system that requires a railway engineer as a domain expert to differentiate between d...

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Autores principales:	Muhammad Shadab Alam Hashmi, Muhammad Ibrahim, Imran Sarwar Bajwa, Hafeez-Ur-Rehman Siddiqui, Furqan Rustam, Ernesto Lee, Imran Ashraf
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2022-03-01
Colección:	Sensors
Materias:	railway track inspection spectrograms acoustic signals machine learning deep convolution neural networks LSTM
Acceso en línea:	https://www.mdpi.com/1424-8220/22/5/1983
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