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学术报告二十五: From Variational Models to Recurrent Neural Network

来源:数学与统计学院     作者:     时间:2017/9/20 17:00:18  0次

数学与统计学院学术报告[2017] 025

(高水平大学建设系列报告095)

讲座题目: From Variational Models to Recurrent Neural Networks For Image Restoration

讲座人:冯文森  华为公司2012实验室高级科学家

讲座时间:2017/9/24  上午10:30-12:00

讲座地点:科技楼515-4                                

报告内容:Image restoration is a long-standing problem in low-level computer vision with many interesting applications. An effective framework for image restoration is to make use of the variational model. Traditional variational models aim at solving a minimization problem using some iterative optimization algorithms which may be relatively time-consuming and therefore challenging for practical applications. Recently, several approaches have been proposed to solve this deficiency. These approaches do not exactly solve the minimization problem anymore, but in contrast, they run the solving optimization algorithm for several steps, and each iterative step is optimized by training. In this presentation, the basic idea of these approaches and their relationship with Recurrent Neural Networks are briefly reviewed. Besides, we also introduce our recent works in this domain.

报告人简历

冯文森,原在北京科技大学任教,现任华为公司2012实验室高级科学家。近年来,在计算机视觉领域重要学术期刊T-CYBT-MMSIAM Imaging等杂志发表论文20余篇。多次担任CVPRICCVECCVNIPSACCVBMVCICIP等会议,及T-IPT-NNLST-CSVTPR等国际著名期刊审稿人。

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