学术活动

大数据邀请报告二十六-Learning Robust Imaging Models without Paired Data

2022-10-11 23:09

报告人: 包承龙

报告人单位: 清华大学

时间: 2022.10.16上午10:00-11:00

地点: 腾讯会议ID138773123

开始时间:

报告人简介: 教授

年:

日月:

The observations in practical imaging systems always contain complex noise such that classical approaches are difficult to obtain satisfactory results. In recent years, deep neural networks directly learned a map between the noisy and clean images based on the training on paired data. Despite its promising results in various tasks, collecting the training data is difficult and time-consuming in practice. In this talk, in the unpaired data regime, we will discuss our recent progress for building AI-aided robust models and their applications in image processing. Leveraging the Bayesian inference framework, our model combines classical mathematical modeling and deep neural networks to improve interpretability. Experimental results on various real datasets validate the advantages of the proposed methods.




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