Research1d ago
Meta-Learning Compression For Microcontroller Object Detection
Under 100KB of memory limits how microcontrollers handle continual object detection. Adaptive Hierarchical Compression uses MAML-based meta-learning to adapt compression ratios via gradient descent in five steps. It employs scale-aware ratios to match FPN redundancy patterns. This framework reduces catastrophic forgetting for practitioners deploying vision models on extreme edge hardware.