AI RESEARCH
Scale-Gest: Scalable Model-Space Synthesis and Runtime Selection for On-Device Gesture Detection
arXiv CS.AI
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ArXi:2605.12506v1 Announce Type: cross Realizing on-device ML-based gesture detection under tight real-time performance, energy and memory constraints is challenging, especially when considering mobile devices with varying battery-power levels. Existing EdgeAI deployments typically rely on a single fixed detector, limiting optimization opportunities. We present Scale-Gest, a novel run-time adaptive gesture detection framework that expands the detector space into a dense family of tiny-YOLO architectures. We.