Yanxin Hu

Papers

Total Citations

162

H-Index

About

Yanxin Hu is a leading researcher in computer vision and robotics, specializing in lightweight object detection algorithms optimized for resource-constrained mobile platforms. Hu’s major contributions center on enhancing the YOLO (You Only Look Once) family of real-time object detectors to achieve high accuracy while dramatically reducing computational overhead—critical for deployment on wheeled mobile robots and embedded systems. Their most influential work, “Lightweight object detection algorithm for robots with improved YOLOv5” (2023), has garnered 149 citations, reflecting its significance in enabling intelligent, real-time perception on devices with limited processing power. Hu’s earlier study, “Object Detection Algorithm for Wheeled Mobile Robot Based on an Improved YOLOv4” (2022), laid the groundwork by addressing the dual challenge of recognizing complex environments while maintaining algorithm efficiency. By pioneering model compression and architectural refinements, Hu has advanced the practical intelligence of autonomous robots, bridging the gap between cutting-edge deep learning and real-world deployment. Their work is essential reading for researchers and students developing vision systems for robotics, edge computing, and autonomous navigation.