[Matching between Lecture & Lab required]
COURSE INFO
PRE-REQUISITEPrerequisites: UFUG 2601 OR UFUG 2602
DESCRIPTIONThis course aims to provide a solid understanding of modern Computer Vision. It starts with essential backgrounds in image processing and classical vision methods, then transitions to contemporary learning-based techniques. Students will master core architectures including CNNs, Transformers, and generative models like GANs and Diffusion. Advanced modules explore detection, segmentation, and learning-based 3D vision. The course emphasizes problem-solving through a practical mini-project, encouraging students to apply these algorithms to real-world needs such as biomedical analysis or AR/VR. Students will finish the course ready to conduct independent research and develop innovative vision solutions.

AIAA 3201 - Introduction to Computer Vision (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L02 (6425) Th 01:30PM - 03:20PMRm 134, E1WANG, Hao484800 
LA02 (6427) Th 03:30PM - 04:20PMRm 134, E1WANG, Hao484800 
COURSE INFO
VECTOR[3-0-0:3]
DESCRIPTIONThis course focuses on the Artificial Intelligence (AI) techniques and applications in multimodal tasks, which involve processing, fusing, and generating contents from multiple data modalities, such as images, videos, text etc. The course will cover the challenges, state-of-the-art methods, as well as hands-on experience in implementing and evaluating multi-modal deep learning models.

AIAA 5048 - Multimodal Artificial Intelligence (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6038) Tu 01:30PM - 04:20PMRm 101, W4WANG, Hao454410