Yiqi Zhuang

Papers

Total Citations

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About

Yiqi Zhuang is a researcher focused on advancing computer vision and robotics, with particular expertise in object detection and region-of-interest (ROI) analysis for intelligent systems. Their most cited work, "A Practical ROI and Object Detection Method for Vision Robot" (2020), addresses a fundamental challenge in visual robotics: how to accurately recognize objects while excluding irrelevant visual information to improve processing speed. By proposing a targeted ROI-based detection framework, Zhuang’s method enhances the efficiency and reliability of robotic perception, enabling faster and more precise decision-making in real-world environments. This contribution is critical for applications ranging from autonomous navigation to industrial automation. With 1 citation, the paper represents an early but promising step in their research trajectory, demonstrating a practical approach to integrating machine learning with robotic vision. Zhuang’s work underscores the importance of optimizing computational resources in vision systems, and their ongoing research continues to explore how intelligent extraction of visual features can bridge the gap between raw sensor data and actionable robotic responses. Their contributions are particularly valuable for students and engineers seeking efficient, real-time solutions in robotics and computer vision.