Xianyi Zhai

Papers

Total Citations

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About

Xianyi Zhai is a leading researcher at the intersection of deep learning and marine robotics, with a primary focus on intelligent aquaculture monitoring and underwater object detection. His most impactful contributions include the development of a multi-target tracking algorithm for aquaculture environments, which leverages advanced deep learning techniques to enable real-time monitoring of aquatic species—a paper that has garnered 37 citations since 2023. Zhai is also widely recognized for his work on underwater sea cucumber identification, where he proposed an improved YOLOv5 architecture to enhance the accuracy and speed of machine vision systems for autonomous sea cucumber collection robots. This study, cited 28 times, addresses critical challenges in underwater localization and species recognition, directly supporting the advancement of marine harvesting automation. Zhai’s research not only pushes the boundaries of computer vision in challenging underwater settings but also provides practical solutions for sustainable aquaculture and robotic harvesting. His work is essential reading for engineers and scientists developing intelligent systems for marine biology and environmental monitoring.