Application of Deep Learning Techniques in Negative Road Anomalies Detection

Jihad Dib; Konstantinos Sirlantzis; Gareth Howells

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Paper

Application of Deep Learning Techniques in Negative Road Anomalies Detection

Topics: Deep Learning; Image and Video Processing; Mobile Robots; Robot Vision

In Proceedings of the 14th International Joint Conference on Computational Intelligence - Volume 1: ROBOVIS, 475-482, 2022 , Valletta, Malta

Authors: Jihad Dib ; Konstantinos Sirlantzis and Gareth Howells

Affiliation: School of Engineering and Digital Arts, Jennison Building, University of Kent, Canterbury CT2 7NT, U.K.

Keyword(s): Pothole Detection, Road Anomaly, Deep Learning, Deep Neural Network, Convolutional Network, Image Processing, Object Detection, Object Classification.

Abstract: Negative Road Anomalies (Potholes, cracks, and other road anomalies) have long posed a risk for drivers driving on the road. In this paper, we apply deep learning techniques to implement a YOLO-based (You Only Look Once) network in order to detect and identify potholes in real-time providing a fast and accurate detection and sufficient time for proper safe navigation and avoidance of potholes. This system can be used in conjunction with any existing system and can be mounted to moving platforms such as autonomous vehicles. Our results show that the system is able to reach real-time processing (29.34 frames per second) with a high level of accuracy (mAP of 82.05%) and detection accuracy of 89.75% when mounted onto an Electric-Powered Wheelchair (EPW).

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Paper citation in several formats:

Dib, J.; Sirlantzis, K. and Howells, G. (2022). Application of Deep Learning Techniques in Negative Road Anomalies Detection. In Proceedings of the 14th International Joint Conference on Computational Intelligence - ROBOVIS; ISBN 978-989-758-611-8; ISSN 2184-3236, SciTePress, pages 475-482. DOI: 10.5220/0011336000003332

@conference{robovis22,
author={Jihad Dib. and Konstantinos Sirlantzis. and Gareth Howells.},
title={Application of Deep Learning Techniques in Negative Road Anomalies Detection},
booktitle={Proceedings of the 14th International Joint Conference on Computational Intelligence - ROBOVIS},
year={2022},
pages={475-482},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011336000003332},
isbn={978-989-758-611-8},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computational Intelligence - ROBOVIS
TI - Application of Deep Learning Techniques in Negative Road Anomalies Detection
SN - 978-989-758-611-8
IS - 2184-3236
AU - Dib, J.
AU - Sirlantzis, K.
AU - Howells, G.
PY - 2022
SP - 475
EP - 482
DO - 10.5220/0011336000003332
PB - SciTePress