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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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
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| 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 |