Zexin Guo

Papers

Total Citations

H-Index

About

Zexin Guo is an emerging researcher in the fields of computer vision and intelligent surveillance, with a primary focus on human target detection and tracking. Their most cited work, "Human Target Detection and Tracking Algorithm Based on Improved YOLOv7" (2023), addresses critical limitations in mainstream detection algorithms by enhancing detection accuracy for human-oriented applications. This contribution holds significant promise for practical fields including medicine and security, where reliable human tracking is essential. Although early in their career—with the paper currently holding 3 citations—Guo’s research demonstrates a keen ability to identify and refine gaps in state-of-the-art models like YOLOv7. Their work represents a meaningful step toward more robust, real-time surveillance systems, and positions them as a promising voice in the ongoing evolution of deep learning-based object detection.