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Found 2 papers, 1 papers with code
Visual Saliency-Guided Channel Pruning for Deep Visual Detectors in Autonomous Driving
Deep neural network (DNN) pruning has become a de facto component for deploying on resource-constrained devices since it can reduce memory requirements and computation costs during inference.
Adversarial Attack and Defense of YOLO Detectors in Autonomous Driving Scenarios
Experiments show that the proposed attack targeting the objectness aspect is 45. 17% and 43. 50% more effective than those generated from classification and/or localization losses on the KITTI and COCO traffic datasets, respectively.
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