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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書誌詳細

主要な著者:	Muhammad Shadab Alam Hashmi, Muhammad Ibrahim, Imran Sarwar Bajwa, Hafeez-Ur-Rehman Siddiqui, Furqan Rustam, Ernesto Lee, Imran Ashraf
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2022-03-01
シリーズ:	Sensors
主題:	railway track inspection spectrograms acoustic signals machine learning deep convolution neural networks LSTM
オンライン･アクセス:	https://www.mdpi.com/1424-8220/22/5/1983
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