Chih-Chang Yu

About

Chih-Chang Yu is a researcher at the forefront of computer vision and autonomous systems, with a primary focus on real-time object detection and tracking for unmanned aerial vehicles (UAVs). His most cited work, “Real-Time Object Detection and Tracking for Unmanned Aerial Vehicles Based on Convolutional Neural Networks” (2023, 12 citations), introduces a robust system built on the Robot Operating System (ROS) that leverages a pruned YOLOv4 architecture. This innovation addresses critical challenges in UAV efficiency, enabling faster and more accurate target tracking in dynamic environments. Yu’s contributions are particularly notable for bridging the gap between lightweight neural network design and practical deployment on resource-constrained drones. By optimizing detection speed without sacrificing precision, his research has significant implications for applications ranging from surveillance to search-and-rescue operations. Though early in his career, Yu’s work demonstrates a clear impact on the field of autonomous robotics, with his paper serving as a key reference for engineers developing real-time vision systems. His achievements highlight a promising trajectory in advancing UAV intelligence and embedded AI solutions.

Research Focus

Key Achievements

Top Papers

1. 1
   Real-Time Object Detection and Tracking for Unmanned Aerial Vehicles Based on Convolutional Neural Networks

   12 citations · 2023

Key Collaborators

Contact & Links