Zhiguang Guan

Papers

Total Citations

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About

Zhiguang Guan is a researcher focused on advancing autonomous underwater robotics and marine technology, with key contributions in underwater target detection and remotely operated vehicle (ROV) design. His most cited work, "An Improved YOLOv5s-Based Scheme for Target Detection in a Complex Underwater Environment" (2023, 18 citations), addresses a critical challenge in seafood aquaculture: enabling automated detection of sea cucumbers, sea urchins, and other marine species in challenging underwater conditions. This innovation reduces the need for dangerous human diver operations by improving the accuracy and speed of computer vision systems in murky, low-visibility environments. Guan also contributed to the development of underwater vehicles, including a "Design of Remote Operated Vehicle Based on STM32" (2021) and an "Analysis of Open Water Performance of Integrated Motor Propeller" (2021), both foundational to efficient, low-cost marine exploration. While his citation counts are early-stage, his work directly supports safer, more sustainable fishing practices and autonomous marine monitoring. Guan’s research sits at the intersection of deep learning, embedded systems, and marine engineering, offering practical solutions for the growing aquaculture industry.