Tackling Clutter in Radar Data - Label Generation and Detection Using PointNet++
Author:
Affiliation:
1. Institute of Measurement, Control and Microtechnology, Ulm University,Ulm,Germany,89081
2. BMW AG,Munich,Germany,80809
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10160211/10160212/10160222.pdf?arnumber=10160222
Reference28 articles.
1. Radar Ghost Target Detection via Multimodal Transformers
2. Anomaly Detection in Radar Data Using PointNets
3. Comparison of Different Approaches for Identification of Radar Ghost Detections in Automotive Scenarios
4. Ghost Target Detection in 3D Radar Data using Point Cloud based Deep Neural Network
5. The Radar Ghost Dataset – An Evaluation of Ghost Objects in Automotive Radar Data
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1. MilliNoise;Proceedings of the ACM Multimedia Systems Conference 2024 on ZZZ;2024-04-15
2. Comparison of Neural Network Architectures for the Detection of Clutter in Automotive Radar Data;2023 23rd International Conference on Control, Automation and Systems (ICCAS);2023-10-17
3. Simultaneous Clutter Detection and Semantic Segmentation of Moving Objects for Automotive Radar Data;2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC);2023-09-24
4. Clutter Detection in Automotive Radar Point Clouds Based on Deep Learning with Self-attention;2023 8th International Conference on Signal and Image Processing (ICSIP);2023-07-08
5. Radars for Autonomous Driving: A Review of Deep Learning Methods and Challenges;IEEE Access;2023
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