报告题目：Curvature regularization：models, algorithms and applications

主  讲 人：段玉萍 教授

单      位：北京师范大学

时      间：2024年6月7日 16:00

地      点：郑州校区九章学堂C座302

摘      要：The geometric high-order regularization methods such as Euler’selatica, mean curvature, and Gaussian curvature, have been intensively studied during the last decades due to their abilities in preserving geometric properties including image edges, corners, and image contrast. However, the dilemma between restoration quality and computational efficiency is an essential roadblock for high-order methods. We propose novel curvature regularization models and develop fast multi-grid algorithms without sacrificing the accuracy for efficiency. Besides, we also extend the application of curvature energies for non-line-of-sight (NLOS) imaging. Both traditional and learnable curvature regularization model are developed for NLOS with under-scanning measurements.

简      介：段玉萍，2012年在新加坡南洋理工大学大学取得计算数学博士学位，之后在新加坡科技研究局资讯通信研究院担任研究科学家。2016年任天津大学应用数学中心教授，博士生导师，2023年加入北京师范大学数学科学学院。主要研究方向包括变分图像处理方法、区域分解算法、模型驱动的深度学习和软组织形变仿真，已在IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing，IEEE Transactions on Medical Imaging，SIAM Journal on Imaging Sciences，Journal of Scientific Computing等重要学术期刊和CVPR，MICCAI，ISBI等国际会议上发表研究论文五十多篇，已授权国际/国内专利4项，先后承担国家自然科学基金项目2项和天津市重大科技专项1项，参与科技部重点研发计划变革性技术关键科学问题项目1项。（邀请人：庞志峰）