Off-the-shelf sensor vs. experimental radar - How much resolution is necessary in automotive radar classification?-Reference-Cited by-同舟云学术

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Off-the-shelf sensor vs. experimental radar - How much resolution is necessary in automotive radar classification?

Published:2020-07 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE 23rd International Conference on Information Fusion (FUSION)
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Author:

Scheiner Nicolas,Schumann Ole,Kraus Florian,Appenrodt Nils,Dickmann Jurgen,Sick Bernhard

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9183728/9190162/09190338.pdf?arnumber=9190338

Cited by 14 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. Automotive Radar Point Cloud Parametric Density Estimation using Camera Images;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

2. RC-BEVFusion: A Plug-In Module for Radar-Camera Bird’s Eye View Feature Fusion;Lecture Notes in Computer Science;2024

3. 3D-Printed Dielectric Rods for Radar Range Enhancement;Electronics;2023-09-23

4. Online Learning-Based Waveform Selection for Improved Vehicle Recognition in Automotive Radar;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

5. Cross-Modal Supervision-Based Multitask Learning With Automotive Radar Raw Data;IEEE Transactions on Intelligent Vehicles;2023-04

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