An Exploration of Object Detection and Vehicular Communication for Autonomous Vehicles
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-69982-5_33
Reference24 articles.
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2. Kumar, V.D.A., Raghuraman, M., Kumar, A., Rashid, M., Hakak, S., Reddy, M.P.K.: Green-tech CAV: next generation computing for traffic sign and obstacle detection in connected and autonomous vehicles. IEEE Trans. Green Commun. Network. 6(3), 1307–1315 (2022). https://doi.org/10.1109/TGCN.2022.3162698
3. Maalej, Y., Sorour, S., Abdel-Rahim, A., Guizani, M.: VANETs meet autonomous vehicles: a multimodal 3D environment learning approach. In: GLOBECOM 2017 - 2017 IEEE Global Communications Conference, Singapore, pp. 1–6 (2017). https://doi.org/10.1109/GLOCOM.2017.8254480
4. Kushwaha, M., Abirami, M.S.: Yolov7-based brake light detection model for avoiding rear-end collisions. In: 2023 12th International Conference on Advanced Computing (ICoAC), Chennai, India, pp. 1–7 (2023). https://doi.org/10.1109/ICoAC59537.2023.10249731
5. Farooq, M., Kanwal, S.: Traffic Road Congestion System using by the internet of vehicles (IoV) (2023)
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