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eess.SP2025
Deep Generative Models for Bayesian Inference on High-Rate Sensor Data: Applications in Automotive Radar and Medical Imaging
Tristan S. W. Stevens, Jeroen Overdevest, Oisín Nolan +3
Deep generative models have been studied and developed primarily in the context of natural images and computer vision. This has spurred the development of (Bayesian) methods that u…
eess.SP2024
Performance Evaluation and Analysis of Thresholding-based Interference Mitigation for Automotive Radar Systems
Jun Li, Jihwan Youn, Ryan Wu +2
In automotive radar, time-domain thresholding (TD-TH) and time-frequency domain thresholding (TFD-TH) are crucial techniques underpinning numerous interference mitigation methods.…