广州数学大讲坛第五期

第五十讲——西安交通大学曾锦山教授学术报告

题目：Model-Data-Driven Hyperspectral Compressive Snapshot Reconstruction Methods

时间：2025年9月12日（星期五）下午15:50-17:00

地点：文新楼603

报告人：曾锦山 教授

摘要：Coded aperture snapshot spectral imaging (CASSI) is an important technique for capturing three-dimensional (3D) hyperspectral images (HSIs), and involves an inverse problem of reconstructing the 3D HSI from its corresponding coded 2D measurements. Existing model-based and learning-based methods either could not explore the implicit feature of different HSIs or require a large amount of paired data for training, resulting in low reconstruction accuracy or poor generalization performance as well as interpretability. In this talk, we introduce two novel model-data-driven HSI reconstruction methods to remedy these deficiencies, through exploiting the global spectral correlation from the HSI itself through a formulation of model-driven low-rank subspace representation and learning the deep priors by some data-driven deep learning schemes. Extensive experiments on several datasets and imaging systems validate the superiority of our methods.

报告人简介：

曾锦山，西安交通大学管理学院青拔A类教授，博士生导师。主持国家自然科学基金3项和江西省自然科学基金杰出青年项目，入选江西省重大人才计划。现已在人工智能相关领域主流期刊和会议上发表高水平论文80余篇，单篇论文最高引用1500余次（谷歌学术）。授权发明专利20余项，荣获江西省自然科学奖二等奖1项（第一完成人）、2025国际基础科学大会“前沿科学奖”、2018和2020“世界华人数学家联盟最佳论文奖”，连续两年入选“中国数学领域热点论文榜单前十”。受邀在2025国际基础科学大会上作60分钟前沿科学奖报告，在数届世界华人数学家大会上作大会特邀报告或专题学术报告。受邀担任国际高水平学术会议副主席或论坛主席10余次。主要研究方向是人工智能中优化算法理论及其应用。