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反问题、不确定性量化与机器学习系列第七场报告通知
发布时间 : 2021-04-28     点击量:

报告题目:Low Dimensional Manifold Model for Image Processing


报告时间:2021年4月30日,星期五,上午9:00-10:00


腾讯会议ID:402 867 393


报告人:史作强 副教授,清华大学


报告摘要:

In this talk, I will present a novel low dimensional manifold model for some image processing problem. This model is based on the observation that for many natural images, the patch manifold usually has low dimension structure. Then, we use the dimension of the patch manifold as a regularization to recover the original image. Using some formula in differential geometry, this problem is reduced to solve Laplace-Beltrami equation on manifold. The Laplace-Beltrami equation is solved by the point integral method. Numerical tests show that this method gives very good results in image inpainting, denoising and super-resolution problem.


报告人简历:

Shi Zuoqiang got his Ph.D. in Applied Mathematics from Tsinghua University in 2008. He was a postdoctoral Scholar at California Institute of Technology in 2008 - 2011. Since 2011, he has been an Associate Professor at Yau Mathematical Sciences Center, Tsinghua University. Prof. Shi's research interests focus on nonlinear and non-stationary data analysis, singularity problems in fluid mechanics, numerical analysis and computation of immersed boundary method, nonlinear wave phenomena in periodic media, and so on. His publication appears in Applied and Computational Harmonic Analysis, Journal of Computational Physics, Advances in Mathematics, Physical Review A, Physical Review E, etc.


腾讯会议信息:

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会议主题:贾骏雄预定的会议

会议时间:2021/04/30 09:00-10:30 (GMT+08:00) 中国标准时间 - 北京

点击链接入会,或添加至会议列表:

https://meeting.tencent.com/s/bJkNwvXq7csK

会议 ID402 867 393


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