Real-Time Asphalt Pothole Detection Using the YOLOv5 Algorithm and the Nvidia Jetson Nano Embedded Board
References
- Balasubramaniam A., Pasricha S., Object Detection in Autonomous Vehicles: Status and Open Challenges, Colorado State University, January 2022, https://arxiv.org/abs/2201.07706, accessed on 22.08.2024.
- Bennett J., Smart AI Pothole Detector, https://developer.nvidia.com/embedded/community/jetson-projects/ai_pothole_detector, accessed on 22.08.2024.
- Kiiskilä M., Kiiskilä P., Evolving Deep Architectures: A New Blend of CNNs and Transformers Without Pre-training Dependencies, In: Fred A., Hadjali A., Gusikhin O., Sansone C. (eds) Deep Learning Theory and Applications, DeLTA, 2024. Communications in Computer and Information Science, vol 2171. Springer, Cham. https://doi.org/10.1007/978-3-031-66694-0_10, accessed on 22.08.2024.
- Singht M., Akoula A., A Comparative Study of YOLO-V5 Variants Performance for Object Detection, 2024 IEEE 5th India Council International Subsections Conference (INDISCON), Chandigarh, India, https://ieeexplore.ieee.org/document/10744406.
- Wu W., Zou X., Fang Z, Fang W., Song X., Yang A., Liu Z., Research on Asphalt Pavement Crack Detection using YOLOv5 Model, 2024 7th International Conference on Advanced Algorithms and Control Engineering (ICAACE), March 2024, Shanghai, China.
- Yu J., Jiang J., Fichera S., Paoletti P., Layzell L., Mehta D., Luo S., Road Surface Defect Detection‒From Image-Based to Non-Image-Based: A Survey, IEEE Transactions on Intelligent Transportation Systems (Early Access), April 2024, 1-23.
Language: English
Page range: 57 - 67
Submitted on: Sep 2, 2024
Accepted on: Dec 29, 2024
Published on: Feb 21, 2025
Published by: Gheorghe Asachi Technical University of Iasi
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
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© 2025 Marius-Emanuel Obreja, Dan-Marius Dobrea, Rareş-Petru Ibănişteanu, published by Gheorghe Asachi Technical University of Iasi
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.