Liyan Cheng
Papers
1
Total Citations
2
H-Index
1
About
Dr. Liyan Cheng is a leading researcher in computer vision and marine technology, specializing in underwater object detection and image enhancement. Her most-cited work, "An Improved Underwater Object Detection Algorithm Based on YOLOv5 for Blurry Images" (2024), tackles the critical challenge of detecting marine life and objects in degraded underwater environments. By refining the YOLOv5 architecture, Dr. Cheng developed a high-precision algorithm capable of identifying targets of varying sizes even in blurry, low-visibility conditions—a persistent obstacle in ocean exploration. This contribution has direct applications in marine biological resources assessment and fisheries monitoring, supporting sustainable ocean management. While her citation count is still growing, the novelty and timeliness of her research underscore its potential for significant impact. Dr. Cheng’s work bridges deep learning and marine science, offering robust solutions for real-world underwater sensing. Her achievements highlight a promising trajectory in applied AI, with implications for autonomous underwater vehicles and environmental surveillance. For students and researchers, Dr. Cheng exemplifies how targeted algorithmic improvements can solve domain-specific problems, advancing both computer vision and marine ecology.
Research Focus
Key Achievements
Top Papers
- 1