M2 Internship: Dynamic Inference in CNNs via Mixture of Experts and Early Exits
Context The deployment of deep neural networks on edge devices such as smartphones or embedded systems poses significant challenges in terms of computational cost, energy consumption, and latency. Traditional models process all inputs with the same fixed architecture, regardless of their complexity, leading to inefficient use of resources. For instance,…


