课程题目: Topics in Image Analysis
授 课 人: Young Ju Lee 教授
所在单位: Texas State University
课程时间:2022年09月27日 - 2022年10月20日
报告摘要: The course goal is to introduce a couple of topics in image analysis. This includes image segmentation, image de-noising and image reconstruction. An in-depth knowledge on some of important topics in image analysis will be presented. The course will be maintained to provide not only algorithmic techniques but also a hands-on experience to implement the algorithms. After students complete the course works, they are expected to have abilities to tackle a number of image analysis problems.
日程安排:
#腾讯会议:581-4300-5514 : Sep/27, Oct/04, Oct/11, Oct/18
#腾讯会议:499-5388-0175 : Sep/29, Oct/06, Oct/13, Oct/20
1. (Sep/27) Introduction of Topics in Image Analysis
2. (Sep/29) Image Segmentation by Normalized Cut
3. (Oct/04) Image Segmentation by Constrained Normalized Cut
4. (Oct/06) Multiscale Image Segmentation
5. (Oct/11) Image Denoising by Bilateral Smoothing
6. (Oct/13) Image Denoising by Constrained Bilateral Smoothing
7. (Oct/18) Dynamic Mode Decomposition
8. (Oct/20) Image Reconstruction via Dynamic Mode Decomposition
基础知识:Advanced Calculus, Linear Algebra and familiarity with differential equations and graph theory. A basic skill to use Matlab is necessary.
报告人简介:Young Ju Lee is a Professor at Texas State University, Mathematics Department. He obtained his Ph.D degree at Penn State and had a prior faculty position at UCLA and Rutgers, The State University of New Jersey. His expertise is at the development of fast solver for partial differential equations. His current research focuses on development of structure preserving finite element discretization for PDE systems. His research has been funded by National Science Foundation and American Chemical Society. The current research is being funded by Korea Brain Pool program by National Research Foundation of Korea.