TensorRT YOLO pipelines on Jetson Nano maintain stable GPU occupancy, power draw, and thermal behavior under heavy input degradation from LLM- and LDM-synthesized faults for both object detection and lane-following tasks.
Improving performance of real-time object detection in edge device through concurrent multi -frame processing,
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Hardware Utilization and Inference Performance of Edge Object Detection Under Fault Injection
TensorRT YOLO pipelines on Jetson Nano maintain stable GPU occupancy, power draw, and thermal behavior under heavy input degradation from LLM- and LDM-synthesized faults for both object detection and lane-following tasks.