Deep learning model compression for resource efficient activity recognition on edge devices University of Antwerp
This paper presents an approach to adapt an existing activity recognition model for efficient deployment on edge devices. The used model, called YOWO (You Only Watch Once), is a prominent deep learning model. Given its computational complexity, direct deployment on resource-constrained edge devices is challenging. To address this, we propose a two-stage compression methodology consisting of structured channel pruning and quantization. The goal ...