Junyan Tian
Papers
1
Total Citations
2
H-Index
1
About
Dr. Junyan Tian is a researcher specializing in efficient computer vision and embedded AI systems, with a particular focus on lightweight object detection for autonomous robotics. Their most notable contribution is the development of an end-to-end lightweight object detection method based on YOLOv5, specifically designed for intelligent sweeping robots. This work addresses the critical challenge of deploying real-time visual perception on resource-constrained devices by introducing a novel co-optimization strategy that combines layer pruning and channel pruning. This approach effectively balances the trade-off between model parameters, floating-point operations (FLOPs), and detection performance, enabling practical deployment in household robotics. While their 2023 publication has garnered initial attention with 2 citations, Dr. Tian’s work represents an important step toward making advanced computer vision algorithms accessible for edge computing applications. Their research sits at the intersection of model compression, real-time object detection, and robotic perception, contributing to the growing field of efficient deep learning for autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1