OpenGlass is an open-source smart glasses platform using event-based vision and event-driven power management to achieve 11.5 hours of continuous on-device ML on a 200 mAh battery, demonstrated with 83.94% cross-subject hand gesture accuracy.
TensorFlow Lite Micro: Embedded machine learning on TinyML systems,
5 Pith papers cite this work, alongside 167 external citations. Polarity classification is still indexing.
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AIGaitor is the first claimed end-to-end on-device monocular motion-capture and deep-learning gait analysis pipeline demonstrated on consumer smartphones.
PhysioLite delivers Transformer-comparable ECG/EMG performance using learnable wavelet filters and hardware-aware design at ~370KB quantized size on μNPUs.
Residual reinforcement learning automates map-based ECU calibration to closely match series production references with minimal human intervention.
Measurement-based characterization of quantized AI inference latency and data movement on Cortex-M platforms, positioned as a lower-bound reference for small-satellite embedded vision workloads.
citing papers explorer
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OpenGlass: Ultra-Low-Power On-Device AI Eyewear with Event-based Vision
OpenGlass is an open-source smart glasses platform using event-based vision and event-driven power management to achieve 11.5 hours of continuous on-device ML on a 200 mAh battery, demonstrated with 83.94% cross-subject hand gesture accuracy.
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AIGaitor: Privacy-preserving and cloud-free motion analysis for everyone, using edge computing
AIGaitor is the first claimed end-to-end on-device monocular motion-capture and deep-learning gait analysis pipeline demonstrated on consumer smartphones.
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Towards Real-Time ECG and EMG Modeling on $\mu$NPUs
PhysioLite delivers Transformer-comparable ECG/EMG performance using learnable wavelet filters and hardware-aware design at ~370KB quantized size on μNPUs.
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Production-Ready Automated ECU Calibration using Residual Reinforcement Learning
Residual reinforcement learning automates map-based ECU calibration to closely match series production references with minimal human intervention.
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Quantized AI Inference on Constrained Embedded Platforms for Small-Satellite Settings
Measurement-based characterization of quantized AI inference latency and data movement on Cortex-M platforms, positioned as a lower-bound reference for small-satellite embedded vision workloads.