Liang-Hua Chen

Fu Jen Catholic University, Institute of Information Science, Academia Sinica

Papers

Total Citations

H-Index

About

Liang-Hua Chen is a pioneering researcher in the field of automated identification and computer vision, with a focused expertise in bar-code recognition systems. His most influential contributions center on the application of neural networks to decode visual data, particularly in challenging, camera-based environments. In his seminal 1995 work, Chen introduced a bar-code recognition system using backpropagation neural networks, laying the groundwork for a technology that would overcome the limitations of traditional laser scanners. His subsequent 2005 paper refined this approach, proposing a camera-based system that could read bar codes at variable distances—a significant advancement over the fixed-distance constraints of laser readers. Though his citation counts (15 and 14, respectively) reflect a specialized niche, the impact of his work is profound, enabling more flexible and cost-effective point-of-sale solutions. Chen’s research bridges pattern recognition and practical retail technology, demonstrating how neural networks can solve real-world imaging problems. His achievements highlight the enduring value of applied machine learning in everyday commerce, making him a notable figure in the evolution of automated identification systems.