Road User Detection on Polarimetric Pre-CFAR Radar Data Level
Author:
Affiliation:
1. Mercedes-Benz AG, Research and Development, Stuttgart, Germany
2. Faculty of Electrical Engineering and Information Technology, Technical University of Chemnitz, Chemnitz, Germany
Funder
Cooperative Project @CITY – Automated Cars and Intelligent Traffic
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/7083369/10102643/10106432.pdf?arnumber=10106432
Reference29 articles.
1. Raw High-Definition Radar for Multi-Task Learning
2. Graph Convolutional Networks for 3D Object Detection on Radar Data
3. Polarimetric Information Representation for Radar based Road User Detection with Deep Learning
4. Classification of objects in polarimetric radar images using CNNs at 77 GHz
5. YOLO v3.0: An incremental improvement;redmon,2018
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