Prof. Chuen-Horng Lin | Computer Science and Information Engineering | Best Researcher Award

National Taichung University of Science and Technology, Taiwan

Author Profile

• Google Scholar Profile

Early Academic Pursuits

Chuen-Horng Lin embarked on his academic journey with a focus on applied mathematics, earning his M.S. and Ph.D. degrees from National Chung-Hsing University in Taiwan. His early research delved into stress and strength analysis, particularly in composite materials, utilizing the Direct Boundary Element Method.

Professional Endeavors

Transitioning into computer science and engineering, Lin has made significant contributions to various fields, including computer vision, image processing, machine learning, deep learning, and pattern recognition. His work has encompassed automated image and video analysis, emphasizing detection, tracking, and segmentation methods.

Contributions and Research Focus

Lin's research has spanned several impactful areas, from the stress analysis of bolted composite joints to the development of fast image retrieval systems. His publications reflect a diverse range of interests, including repairable systems, fuzzy analysis of queueing systems, and parametric programming approaches for batch arrival queues. Notably, his work has been published in prestigious journals and conference proceedings, garnering citations and recognition within the scientific community.

Accolades and Recognition

Lin's contributions have not gone unnoticed, as evidenced by his publications in renowned journals and his citation impact. His research has been acknowledged for its innovation and relevance, earning him accolades within his field.

Impact and Influence

Through his interdisciplinary work, Lin has left a significant impact on the fields of computer science, engineering, and applied mathematics. His contributions have advanced methodologies in image analysis, system modeling, and optimization techniques, shaping the trajectory of research in these domains.

Legacy and Future Contributions

Lin's legacy lies in his multidisciplinary approach to problem-solving and his dedication to advancing knowledge at the intersection of computer science and engineering. As he continues his academic journey, his future contributions are poised to further enrich our understanding of complex systems and drive innovation in computational methods.

Notable Publications 

Classification of the tree for aerial image using a deep convolution neural network and visual feature clustering