Qilong Zhou

Jiangsu University of Science and Technology

Papers

Total Citations

H-Index

About

Qilong Zhou is a researcher at the forefront of underwater robotics and computer vision, with a focus on advancing autonomous systems for marine exploration. His most-cited work, "Underwater Robot Target Detection Algorithm Based on YOLOv8" (2024, 13 citations), tackles the formidable challenges of low visibility, color distortion, and dynamic lighting in subsea environments. By enhancing the YOLOv8 architecture, Zhou introduced novel modifications that significantly improve detection accuracy and speed, enabling robots to identify objects—such as marine life, debris, or infrastructure—with greater reliability. This contribution is critical for applications in oceanography, environmental monitoring, and offshore industry. While his citation count is still growing, reflecting the recent publication of his key paper, Zhou’s work demonstrates a clear impact by addressing a persistent bottleneck in underwater autonomy. His research bridges deep learning and robotics, offering practical solutions for real-world deployment. As the field expands, Zhou’s innovations are poised to influence next-generation underwater vehicles, making him a promising voice in the intersection of AI and marine technology.