Computer Vision: Algorithms and Applications
This course provides foundational algorithms and practical applications in the fields of image processing and computer vision. Topics covered include the fundamental concepts of image formation, essential techniques in image processing, feature detection methodologies, and classical image reconstruction problems such as denoising, deblurring, super-resolution, etc. Additionally, the course introduces several deep learning-based models in image processing and computer vision.
讲师
日期
2024年07月09日 至 02日
位置
| Weekday | Time | Venue | Online | ID | Password |
|---|---|---|---|---|---|
| 周四 | 09:50 - 12:15 | A3-2-301 | ZOOM 2 | 638 227 8222 | BIMSA |
修课要求
None
课程大纲
1. Introduction and image formation
2. Basic image processing
3. Image reconstruction
4. Deep learning
5. Image compression
6. Image compression
7. Morphological image processing
8. Image segmentation
9. Feature detection
10. KAN and U-KAN
11. Mixed selection
2. Basic image processing
3. Image reconstruction
4. Deep learning
5. Image compression
6. Image compression
7. Morphological image processing
8. Image segmentation
9. Feature detection
10. KAN and U-KAN
11. Mixed selection
参考资料
[1] Szeliski, Richard. Computer vision: algorithms and applications, Second edition. Springer Nature, 2022.
[2] Rafael, C. Gonzalez, and E. Woods Richard. Digital image processing, Fourth edition. Pearson education, 2018.
[2] Rafael, C. Gonzalez, and E. Woods Richard. Digital image processing, Fourth edition. Pearson education, 2018.
听众
Undergraduate
, Advanced Undergraduate
, Graduate
, 博士后
, Researcher
视频公开
公开
笔记公开
公开
语言
中文