主 题: Multiscale Analysis Based Texture Classification
报告人: 董永生副教授 (河南科技大学)
时 间: 2016-11-28 15:00-16:00
地 点: 304am永利集团理科1号楼1365(2016信息科学系列报告)
In this report, two multiscale analysis based texture classification methods will be present and discussed. The first is to perform texture classification by modeling the dependence of shearlet subbands. Moreover, this method can also be used for texture retrieval when using a pseudo-feedback mechanism. The second method is to construct a Nonnegative Multiresolution Representation of image textures for classification. In this method, a Heterogeneous and Incrementally Generated Histogram (HIGH) and a Hessian regularized discriminative nonnegative matrix factorization are proposed to compute a compact representation of image textures. 报告人介绍： Yongsheng Dong（董永生）received his Ph. D. degree in applied mathematics from Peking University in 2012. From 2013 to 2016, He was a postdoctoral researcher with the Center for Optical Imagery Analysis and Learning, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China. He is currently an associate professor with Henan University of Science and Technology. His current research interests include pattern recognition, machine learning, and computer vision. He has authored and co-authored over 20 journal and conference papers, including IEEE-TIP, IEEE-TCYB, and ACM-TIST. He has served as a reviewer for over 20 international prestigious journals, such as IEEE-TNNLS, IEEE-TIP, IEEE-TCYB, IEEE-TIE, IEEE-TSP, IEEE-TKDE, IEEE-TCDS, and ACM-TIST. He has also served as a Program Committee Member for over ten international conferences. He is a member of the IEEE, ACM and CCF.
