An AI-Driven System for Identifying Dangerous Driving Vehicles

Author:

Tanaka Hibiki,Shimomura Kazuki,Tanaka Naoki,Ikeda MakotoORCID,Barolli LeonardORCID

Publisher

Springer Nature Switzerland

Reference19 articles.

1. Kaggle: Data science community. https://www.kaggle.com/

2. Roboflow: The world’s largest collection of open source computer vision datasets and apis. https://universe.roboflow.com/

3. Bochkovskiy, A., Wang, C.Y., Liao, H.Y.M.: YOLOv4: Optimal speed and accuracy of object detection. Computer Vision and Pattern Recognition (cs.CV), April 2020. https://arxiv.org/abs/2004.10934

4. Cabinet Office, G.o.J.: 2023 white paper on traffic safety (2023). https://www8.cao.go.jp/koutu/taisaku/r05kou_haku/index_zenbun_pdf.html

5. Chen, G., Wang, F., Li, W., Hong, L., Conradt, J., Chen, J., Zhang, Z., Lu, Y., Knoll, A.: NeuroIV: neuromorphic vision meets intelligent vehicle towards safe driving with a new database and baseline evaluations. IEEE Trans. Intell. Transp. Syst. 23(2), 1171–1183 (2022). https://doi.org/10.1109/TITS.2020.3022921

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