Multi-level Road Damage Identification Algorithm Based on Vehicle-Mounted Smartphone

Author:

Ma DengORCID,Gao KaiORCID,Du RonghuaORCID

Publisher

Springer Nature Singapore

Reference19 articles.

1. Ministry of Transport of the People's Republic of China: In: 2019 Statistical Bulletin on the Development of the Transport Industry. China Communications News (2020) (Chinese)

2. Wahlström, J., Skog, I., Händel, P.: Smartphone-based vehicle telematics: a ten-year anniversary. IEEE Trans Intell Transport Syst (2017)

3. Quintana M, Torres J, Menéndez JM (2016) A simplified computer vision system for road surface inspection and maintenance. 17(3):608–619

4. Ai-min, S.: Recognition and measurement of pavement disasters based on convolutional neural networks. China J Highway Transport 31(01), 1–10 (2018). (Chinese)

5. Li, W., Burrow, M., Li, Z.: Automatic road condition assessment by using point laser sensor. In: 2018 IEEE Sensors, pp. 1–4. IEEE, New Delhi (2018)

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1. Vehicle Damage Identification using Deep Learning Techniques;2024 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS);2024-02-24

2. Efficient dense attention fusion network with channel correlation loss for road damage detection;IET Intelligent Transport Systems;2023-04-19

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