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.
InProceedings of the Second Conference on Machine Learning and Systems, SysML 2019, Stanford, CA, USA, March 31 - April 2, 2019(2019), A
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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.