Automotive surface identification system

Aleksandr Bystrov, Edward Hoare, Thuy-Yung Tran, Nigel Clarke, Marina Gashinova, Mikhail Cherniakov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


In this paper the practical issues of automotive surface identification system development are considering. The novelty of this work is the combining of different training algorithms, neural network structures and methods to increase the classification accuracy and avoid overfitting of real-world data. The obtained results thereby demonstrate that the use of proposed system architecture and statistical methods allow for reliable discrimination of various road surfaces in real driving condition.
Original languageEnglish
Title of host publicationVehicular Electronics and Safety (ICVES), IEEE International Conference on
PublisherIEEE Xplore
Number of pages6
Publication statusPublished - 27 Jul 2017


  • sonar applications
  • Remote Sensing
  • Artificial neural network
  • parameter extraction


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