The Model Efficiency Pipeline: Enabling Deep Learning Inference at the Edge

Explore a comprehensive keynote presentation from the tinyML EMEA 2021 conference focusing on the model efficiency pipeline for enabling deep learning inference at the edge. Delve into the challenges of deploying AI applications on low-power edge devices and wearable platforms, and discover a systematic approach to optimize deep learning models. Learn about Hardware-Aware Neural Architecture Search, compression and pruning techniques, and state-of-the-art quantization tools. Gain insights into mixed-precision hardware-aware neural architecture search and conditional processing as future trends in efficient edge computing. Examine real-world examples, key results, and practical applications across various domains, including video processing and semantic segmentation.