Papers
1
Total Citations
6
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1
About
Yurong Zou is a leading researcher in computer vision and autonomous systems, with a primary focus on small object detection in traffic scenes for mobile robots. Their most-cited work, "Small Object Detection in Traffic Scenes for Mobile Robots: Challenges, Strategies, and Future Directions" (2025, 6 citations), systematically addresses the critical difficulties of detecting small, low-resolution targets under constrained computational resources and highly dynamic environments. Zou’s major contribution lies in identifying and categorizing the unique obstacles—such as weak semantic cues, frequent occlusion, and limited hardware—that hinder reliable perception in real-world robotics. By proposing a comprehensive framework of strategies and future research directions, this work has quickly become a foundational reference for engineers and researchers developing safer, more efficient autonomous navigation systems. Zou’s impact is evident in the paper’s rapid citation uptake, signaling its importance to the field. Their research bridges the gap between theoretical detection algorithms and practical deployment on mobile platforms, offering actionable insights for improving traffic scene understanding. As a rising voice in vision-based robotics, Yurong Zou continues to shape how small objects are perceived in cluttered, fast-moving environments.
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Top Papers
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