| PRE-REQUISITE | Prerequisites: UFUG 2601 OR UFUG 2602 |
|---|---|
| DESCRIPTION | This 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L02 (6936) | We 09:00AM - 10:50AM | Lecture Hall B | ZHAO, Tianxiang | 100 Quota/Enrol/Avail UG Year 3&4 AI students: 100/0/100 | 0 | 100 | 0 | |
| LA02 (6937) | Th 04:30PM - 05:20PM | Lecture Hall B | ZHAO, Tianxiang | 100 | 0 | 100 | 0 |