Regional feature fusion for on-road detection of objects using camera and 3D-LiDAR in high-speed autonomous vehicles-Reference-Cited by-同舟云学术

Regional feature fusion for on-road detection of objects using camera and 3D-LiDAR in high-speed autonomous vehicles

Published:2023-10-03 Issue:23 Volume:27 Page:18195-18213
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Wu Qingyu,Li Xiaoxiao,Wang Kang,Bilal Hazrat

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s00500-023-09278-3.pdf

Reference49 articles.

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2. Cai Y, Luan T, Gao H et al. (2021) YOLOv4–5D: an effective and efficient object detector for autonomous driving, In: IEEE Transactions on Instrumentation and Measurement, vol. 70

3. Cao Z, Liu J, Zhou W, Jiao X, Yang D (2021) LiDAR-based object detection failure tolerated autonomous driving planning system, In: 2021 IEEE Intelligent Vehicles Symposium (IV), Nagoya, Japan, pp 122–128

4. Carranza-García M, Lara-Benítez P, García-Gutiérrez J, Riquelme JC (2021) “Enhancing object detection for autonomous driving by optimizing anchor generation and addressing class imbalance. Neurocomputing 449:229–244

5. Chandra R et al (2020) Forecasting Trajectory and behavior of road-agents using spectral clustering in graph-LSTMs. IEEE Robot Auto Lett 5(3):4882–4890

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