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Found 6 papers, 1 papers with code
Impact of Video Compression Artifacts on Fisheye Camera Visual Perception Tasks
It is essential to prove that lossy video compression artifacts do not impact the performance of the perception algorithms.
Automotive RADAR sub-sampling via object detection networks: Leveraging prior signal information
Automotive radar has increasingly attracted attention due to growing interest in autonomous driving technologies.
Deep learning model compression using network sensitivity and gradients
Deep learning model compression is an improving and important field for the edge deployment of deep learning models.
End-to-end system for object detection from sub-sampled radar data
We show robust detection based on radar data reconstructed using 20% of samples under extreme weather conditions such as snow or fog, and on low-illuminated nights.
Automotive Radar Data Acquisition using Object Detection
In this paper, we introduce an algorithm to utilize object detection results from the image to adaptively sample and acquire radar data using Compressed Sensing (CS).
Adaptive Automotive Radar data Acquisition
We use previous radar frame information to mitigate the potential information loss of an object missed by the image or the object detection network.
