Freespace Optical Flow Modeling for Automated Driving-Reference-Cited by-同舟云学术

Freespace Optical Flow Modeling for Automated Driving

Published:2023 Issue: Volume: Page:1-10
ISSN:1083-4435
Container-title:IEEE/ASME Transactions on Mechatronics
language:
Short-container-title:IEEE/ASME Trans. Mechatron.

Author:

Feng Yi¹^ORCID,Zhang Ruge²^ORCID,Du Jiayuan¹^ORCID,Chen Qijun¹^ORCID,Fan Rui¹^ORCID

Affiliation:

1. College of Electronics and Information Engineering, Shanghai Research Institute for Intelligent Autonomous Systems, State Key Laboratory of Intelligent Autonomous Systems, and Frontiers Science Center for Intelligent Autonomous Systems, Tongji University, Shanghai, China

2. High-Performance Computer Research Center, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Science and Technology Commission of Shanghai Municipal

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/3516/4785241/10224328.pdf?arnumber=10224328

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Evolutionary End-to-End Autonomous Driving Model With Continuous-Time Neural Networks;IEEE/ASME Transactions on Mechatronics;2024-08

2. SG-RoadSeg: End-to-End Collision-Free Space Detection Sharing Encoder Representations Jointly Learned via Unsupervised Deep Stereo;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

3. Cyber‐physical‐based welding systems: Components and implementation strategies;IET Cyber-Physical Systems: Theory & Applications;2024-05

4. SwinMotionSeg: A Point Cloud Moving Object Segmentation Model Based on Swin-Transformer;2023 IEEE International Conference on Imaging Systems and Techniques (IST);2023-10-17