KD-Judge structures fitness rules via LLM retrieval and chain-of-thought, then uses pose-guided kinematics for rule-based rep validation with caching for efficient edge deployment, achieving RTF < 1 and speedups up to 15.91x on Jetson.
Rag-har: Retrieval augmented generation-based human activity recognition
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TRACE improves activity recognition accuracy and temporal coherence in smart homes by integrating multi-source sensor evidence with contextual priors.
citing papers explorer
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KD-Judge: A Knowledge-Driven Automated Judge Framework for Functional Fitness Movements on Edge Devices
KD-Judge structures fitness rules via LLM retrieval and chain-of-thought, then uses pose-guided kinematics for rule-based rep validation with caching for efficient edge deployment, achieving RTF < 1 and speedups up to 15.91x on Jetson.
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TRACE: Temporal Reasoning over Context and Evidence for Activity Recognition in Smart Homes
TRACE improves activity recognition accuracy and temporal coherence in smart homes by integrating multi-source sensor evidence with contextual priors.