Xiang Ma | Computer Science and Artificial Intelligence | Best Researcher Award

Mr. Xiang Ma | Computer Science and Artificial Intelligence | Best Researcher Award

Postgraduate sichuan unviersity China

๐Ÿ“– Xiang Ma is a student at Sichuan University specializing in Electronic Information and Control Engineering. His research focuses on developing innovative solutions for image super-resolution reconstruction in construction site scenarios. By leveraging computer vision, machine learning, and engineering principles, Xiang’s work aims to improve image quality, safety, and monitoring efficiency in real-world construction environments.

Profile

Orcid

Education

๐ŸŽ“ Xiang Ma is pursuing a degree in Electronic Information and Control Engineering at Sichuan University. With a strong academic foundation, he integrates principles of electronic systems, computer vision, and machine learning in his research.

Experience

๐Ÿ”ง Xiang Ma has contributed to three completed and ongoing research projects, including collaborations with CSCEC First Bureau Technology R&D Program and the Sichuan Province Major Special Project on Intelligent Manufacturing and Robotics. His work bridges academic research with industrial applications in safety and automation technologies for construction sites.

Research Interest

๐Ÿ” Xiang Ma is passionate about Image Super-Resolution Reconstruction, with a focus on enhancing low-resolution images affected by noise in construction scenarios. His research includes proposing the Lightweight Feature Enhancement Network (LFEN) to improve visual perception, edge detection, and noise immunity using advanced machine learning techniques.

Awards

๐Ÿ† Xiang Ma is applying for the Best Researcher Award for his contributions to image processing technologies in construction scenarios. His work has been recognized for its innovative approach to leveraging lightweight network designs for practical applications.

Publications Top Notes:ย 

๐Ÿ“š Xiang Ma has published three research papers in prestigious journals:

Liu, Y., Ma, X. & Cheng, J. (2024). Lightweight Feature Enhancement Network for Image Super-Resolution Reconstruction at Construction Sites. Arab Journal of Science and Engineering. Published Year: 2024. Cited by: 15 articles.