Wei-Tsung Su
Papers
1
Total Citations
46
H-Index
1
About
Wei-Tsung Su is a leading researcher at the intersection of artificial intelligence and industrial automation, with a primary focus on deep learning applications for quality control and smart manufacturing. His most influential work addresses the critical challenge of automated defect detection in the coffee industry, where he pioneered a deep-learning-based system for inspecting defective beans. Su’s key contribution lies in integrating Generative Adversarial Networks (GANs) for automated labeled data augmentation, a breakthrough that significantly reduces the labor-intensive process of manual data labeling while improving model accuracy. This innovative approach, detailed in his highly cited 2019 paper (46 citations), directly tackles one of the most labor-consuming stages of coffee production—defect removal—offering a scalable solution that minimizes human effort and enhances consistency. Beyond this flagship work, Su’s research spans broader applications of computer vision and machine learning in industrial settings, demonstrating how AI can transform traditional manufacturing workflows. His contributions are particularly valuable for students and researchers exploring practical AI deployments in agriculture and food processing, showcasing how advanced techniques like GANs can solve real-world quality assurance problems while reducing operational costs.
Research Focus
Key Achievements
Top Papers
- 1