Deeplite Blog ActNAS: Generating efficient YOLO Models with Mixed Activation Functions

This blog is a summary of the research paper Sah, Sudakar, et al. "ActNAS: Generating Efficient YOLO Models using Activation NAS", accepted at the NeurIPS 2024 FITML Workshop. In the ever-evolving field of computer vision, the YOLO family of models has set benchmarks for real-time object detection. However, the quest for higher accuracy often leads to increased model complexity and latency, posing challenges for deployment on edge devices. To address these challenges, Deeplite has introduced a novel approach called Activation NAS (ActNAS) to optimize YOLO models (and applicable to other CNN models as well) by leveraging mixed activation functions tailored to specific hardware.