Linhan Zheng
Papers
1
Total Citations
74
H-Index
1
About
Linhan Zheng is an emerging researcher specializing in computer vision and deep learning, with a particular focus on object detection in challenging underwater environments. Their most notable contribution, "YOLOv8-C2f-Faster-EMA: An Improved Underwater Trash Detection Model Based on YOLOv8," published in 2024, has already garnered an impressive 74 citations — a remarkable achievement for such a recently published work, signaling its immediate relevance and impact within the research community. This paper advances the field of environmental monitoring by proposing an enhanced detection architecture tailored to identify anthropogenic waste in aquatic settings, addressing critical concerns surrounding water quality degradation, ecological harm, and human health risks. By building upon the state-of-the-art YOLOv8 framework and integrating novel architectural improvements, Zheng's work bridges the gap between advanced machine learning methodologies and real-world underwater robotic applications. Their research holds meaningful implications for autonomous environmental remediation systems and sustainable ocean conservation efforts. Though early in their academic career, Linhan Zheng has demonstrated a compelling ability to translate deep learning innovation into practical, socially impactful solutions for pressing environmental challenges.
Research Focus
Key Achievements
Top Papers
- 1