Scale-Gest creates a runtime-selectable family of tiny-YOLO models with device-calibrated ACE profiles and an ROI gate that cuts per-frame energy by 4x while holding event-level F1 at 0.8-0.9 on a new driving-gesture dataset.
J.Deep compression: Compressing deep neural network with pruning, trained quantization and huffman coding.arXiv: Computer Vision and Pattern Recognition(2015)
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Scale-Gest: Scalable Model-Space Synthesis and Runtime Selection for On-Device Gesture Detection
Scale-Gest creates a runtime-selectable family of tiny-YOLO models with device-calibrated ACE profiles and an ROI gate that cuts per-frame energy by 4x while holding event-level F1 at 0.8-0.9 on a new driving-gesture dataset.