CNN architectures for road surface wetness classification from acoustic signals

CNN architectures for road surface wetness classification from acoustic signals

The classification of road surface wetness is important for both the development of future driverless vehicles and the development of existing vehicle active safety systems. Wetness on the road surface has an impact on road safety and is one of the leading causes of weather-related accidents. Alth...

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Bibliographic Details
Main Authors: Bahrami, Siavash, Doraisamy, Shyamala, Azman, Azreen, Nasharuddin, Nurul Amelina, Yue, Shigang
Format: Article
Language:English
Published: Springer
Online Access:http://psasir.upm.edu.my/id/eprint/104489/1/CNN%20Architectures%20for%20Road%20Surface%20Wetness%20Classification%20from%20Acoustic%20Signals.pdf
http://psasir.upm.edu.my/id/eprint/104489/
https://link.springer.com/chapter/10.1007/978-981-16-8515-6_59
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Institution: Universiti Putra Malaysia
Language: English

Internet

http://psasir.upm.edu.my/id/eprint/104489/1/CNN%20Architectures%20for%20Road%20Surface%20Wetness%20Classification%20from%20Acoustic%20Signals.pdf
http://psasir.upm.edu.my/id/eprint/104489/
https://link.springer.com/chapter/10.1007/978-981-16-8515-6_59

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