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Regularization for Hybrid N-Bit Weight Quantization of Neural Networks on Ultra-Low Power Microcontrollers

We propose a novel regularization method for hybrid quantization of neural networks, enabling efficient deployment on ultra-low power microcontrollers in embedded systems. Our approach introduces alternative regularization functions and a uniform …

TinyMLOps for real-time ultra-low power MCUs applied to frame-based event classification

TinyML applications such as speech recognition, motion detection, or anomaly detection are attracting many industries and researchers thanks to their innovative and cost-effective potential. Since tinyMLOps is at an even earlier stage than MLOps, the …