VIC Lab
Affiliations. Department of Electrical Engineering, R70935, Yuan Ze University, Taiwan
The Vision and Intelligent Computing (VIC) Lab is a research laboratory within the Department of Electrical Engineering, dedicated to advancing both fundamental and applied research in computer vision, multimedia processing, artificial intelligence (AI), and intelligent computing. Our research emphasizes the principled integration of image, video, and audio understanding with modern deep learning architectures, representation learning techniques, and intelligent system design.
The mission of our Lab is to develop intelligent, efficient, and scalable AI-driven solutions that address critical challenges across a broad range of application domains. The laboratory consists of undergraduate and graduate students who actively conduct research in computer vision and related AI fields, with applications including healthcare analytics, geoscience and environmental monitoring, human–computer interaction, and autonomous intelligent systems.
The VIC Lab welcomes motivated graduate students, research interns, and collaborators who are interested in joining our research activities. Prospective members are encouraged to contact us via email to discuss research opportunities, including graduate study, internships, and formal research collaborations.
The VIC Lab actively collaborates with international academic institutions, industrial partners, and interdisciplinary research communities. Through these collaborations, we aim to bridge the gap between fundamental research and real-world applications, fostering innovation that contributes to both scientific advancement and broader societal impact.
News
VIC Lab Wins Best Paper Award at ICCE-TW 2026
VIC Lab received the Best Paper Award at ICCE-TW 2026 and presented three collaborative research papers with international partners.
Read more →“Zero-Shot Representation Learning for Alzheimer’s Disease MRI via Frozen CLIP.”
Congratulations to Chun-Yi!
Latest Publications
- CBM
Enhancing the Reliability of Alzheimer’s Disease Prediction in MRI ImagesComputers in Biology and Medicine, 2025 - JAG
ConSeisDiff: A Conditional Diffusion Approach to Mitigate Synthetic–Real Disparities in Seismic Fault DetectionJournal of Applied Geophysics, 2025