贾志刚教授受邀进行讲座

发布时间: 2025-12-16 19:15:00

题      目：A Novel Wasserstein Quaternion Generative Adversarial Network for Color Image Generation

报  告  人：贾志刚 教授  (邀请人：彭小飞)

                                      江苏师范大学

时      间： 12月16日  15：30-16:30

地     点：数科院东楼401

报告人简介:

       贾志刚，江苏师范大学数学与统计学院、数学研究院，教授、博导。2009年毕业于华东师范大学数学系，获理学博士学位；2023年入选江苏高校“青蓝工程”中青年学术带头人；2024年起担任学术期刊Numerical Algorithms的编委。主要研究方向为数值代数与图像处理，至今已在IEEE Trans. Image Process.，SIAM J. Matrix Anal. Appl., SIAM J. Sci. Comput., SIAM J. Imaging Sci. 等期刊上发表学术论文50余篇，其中2 篇入选“ESI高被引”论文；在科学出版社（北京）出版英文专著1部（独立作者）；主持国家自然科学基金项目3项、省高校自然科学研究重大项目1项，参加国家自然科学基金重大项目和国家重点研发计划课题各1项；先后以第一完成人身份荣获第十届淮海科学技术奖（科技创新奖）一等奖和江苏省高等学校科学技术研究成果奖（自然科学奖）三等奖。曾到英国曼彻斯特大学、香港浸会大学、澳门大学等高校数学系进行学术访问

摘      要：

       Color image generation has a wide range of applications, but the existing generation models ignore the correlation among color channels, which may lead to chromatic aberration problems. In addition, the data distribution problem of color images has not been systematically elaborated and explained, so that there is still the lack of the theory about measuring different color images datasets. In this talk, we define a new quaternion Wasserstein distance and develop its dual theory. To deal with the quaternion linear programming problem, we derive the strong duality form with helps of quaternion convex set separation theorem and quaternion Farkas lemma. With using quaternion Wasserstein distance, we propose a novel Wasserstein quaternion generative adversarial network. Experiments demonstrate that this novel model surpasses both the (quaternion) generative adversarial networks and the Wasserstein generative adversarial network in terms of generation efficiency and image quality.