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L. Ambrosini, L. Gabrielli, F. Vesperini, S. Squartini, and L. Cattani, "Deep Neural Networks for Road Surface Roughness Classification from Acoustic Signals," Paper 9934, (2018 May.). doi: L. Ambrosini, L. Gabrielli, F. Vesperini, S. Squartini, and L. Cattani, "Deep Neural Networks for Road Surface Roughness Classification from Acoustic Signals," Paper 9934, (2018 May.). doi:
Abstract: Vehicle noise emissions are highly dependent on the road surface roughness and materials. A classification of the road surface conditions may be useful in several regards, from driving assistance to in-car audio equalization. With the present work we exploit deep neural networks for the classification of the road surface roughness using microphones placed inside and outside the vehicle. A database is built to test our classification algorithms and results are reported, showing that the roughness classification is feasible with the proposed approach.

@article{ambrosini2018deep,
author={ambrosini, livio and gabrielli, leonardo and vesperini, fabio and squartini, stefano and cattani, luca},
journal={journal of the audio engineering society},
title={deep neural networks for road surface roughness classification from acoustic signals},
year={2018},
volume={},
number={},
pages={},
doi={},
month={may},} @article{ambrosini2018deep,
author={ambrosini, livio and gabrielli, leonardo and vesperini, fabio and squartini, stefano and cattani, luca},
journal={journal of the audio engineering society},
title={deep neural networks for road surface roughness classification from acoustic signals},
year={2018},
volume={},
number={},
pages={},
doi={},
month={may},
abstract={vehicle noise emissions are highly dependent on the road surface roughness and materials. a classification of the road surface conditions may be useful in several regards, from driving assistance to in-car audio equalization. with the present work we exploit deep neural networks for the classification of the road surface roughness using microphones placed inside and outside the vehicle. a database is built to test our classification algorithms and results are reported, showing that the roughness classification is feasible with the proposed approach.},}

TY - paper
TI - Deep Neural Networks for Road Surface Roughness Classification from Acoustic Signals
SP - EP -
AU - Ambrosini, Livio
AU - Gabrielli, Leonardo
AU - Vesperini, Fabio
AU - Squartini, Stefano
AU - Cattani, Luca
PY - 2018
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2018 TY - paper
TI - Deep Neural Networks for Road Surface Roughness Classification from Acoustic Signals
SP - EP -
AU - Ambrosini, Livio
AU - Gabrielli, Leonardo
AU - Vesperini, Fabio
AU - Squartini, Stefano
AU - Cattani, Luca
PY - 2018
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2018
AB - Vehicle noise emissions are highly dependent on the road surface roughness and materials. A classification of the road surface conditions may be useful in several regards, from driving assistance to in-car audio equalization. With the present work we exploit deep neural networks for the classification of the road surface roughness using microphones placed inside and outside the vehicle. A database is built to test our classification algorithms and results are reported, showing that the roughness classification is feasible with the proposed approach.