以诚为本赢在信誉9001cc65周年校庆系列报告（10.17—10.21）

10月19日：张小群：Wavelet Frame based Image Segmentation

报告题目：Wavelet Frame based Image Segmentation

报告人：张小群 研究员

主持人：周爱民 副教授

报告时间 ：2016年10月19日10:00-11:00

报告地点：中山北路3663号理科大楼B816室

报告摘要：Wavelet frames have been successfully applied in various image restoration problems, such as denoising, inpainting, deblurring, etc. However, they are rarely used in geometric applications. Motivated by recently established theoretical connection between wavelet frame based and total variation based image restoration models, we propose here a convex multi-phase segmentation model based on wavelet frame transform. The connection between solutions of the convexied model and the original binary constrained one is established.   Numerical results show that our method can extract many more details than existing variational methods especially when the image contains different scales of structures. The proposed method can be parallelized easily and its efficiency is further improved by a GPU implementation. In addition, we adapt the model for region of interest tracking for ultrasound video segmentation, on incorporating different noise statistics and sequential distance shape priors. The proposed individual frame nonconvex segmentation model is solved by a proximal alternating minimization algorithm and the convergence of the scheme is established based on the recently proposed Kurdyka-Lojasiewicz property. The numerical tests on two real ultrasound video data sets show that the proposed method achieve better results compared to related level sets models and edge indicator shape priors, in terms of both segmentation quality and computational time. 

报告人简介：张小群，中组部基础人才拔尖计划获得者。法国南布列塔尼大学数学与应用数学博士，2007-2010 期 间在加州大学洛杉矶分校数学系任访问助理教授，2010年 加入上海交通大学数学系与自然科学研究院任特别研究员，主要研究方向包括数学图像处理，计算反问题，最优化理论与算法，计算机视觉，医学图像处理等。

10月19日：Ching Y. Suen：Beauty and the Computer(院士报告)

讲座题目：Beauty and the Computer

主讲人：Ching Y. Suen教授 (加拿大皇家科学院院士, IEEE Fellow, IAPR Fellow)

主持人：吕岳 教授

开始时间：2016-10-19   15:00pm

讲座地址：中北校区理科大楼B914

主办单位：计算机科学与以诚为本赢在信誉9001cc 科技处

报告人简介：

Dr. Ching Y. Suen is the Director of CENPARMI and the Concordia Honorary Chair on AI & Pattern Recognition. He received his Ph.D. degree from UBC Vancouver) and his Master's degree from the University of Hong Kong. He has served as the Chairman of the Department of Computer Science and as the Associate Dean (Research) of the Faculty of Engineering and Computer Science of Concordia University.

Prof. Suen has served at numerous national and international professional societies as President, Vice-President, Governor, and Director. He has given 45 invited/keynote and 260 regular papers at conferences and 200 invited talks at various industries and academic institutions around the world. He has been the Principal Investigator or Consultant of 30 industrial projects. His research projects have been funded by the ENCS Faculty and the Distinguished Chair Programs at Concordia University, FCAR (Quebec), NSERC (Canada), the National Networks of Centres of Excellence (Canada), the Canadian Foundation for Innovation, and the industrial sectors in various countries, including Canada, France, Japan, Italy, and the United States.

Prof. Suen has published 5 conference proceedings, 14 books and more than 500 papers, and many of them have been widely cited while the ideas in others have been applied in practical environments involving handwriting recognition, thinning methodologies, font analysis and multiple classifiers. Dr. Suen is the recipient of numerous awards, including the Gold Medal from the University of Bari (Italy 2012), the IAPR ICDAR Award (2005), the ITAC/NSERC national award (1993), and the "Concordia Lifetime Research Achievement" and "Concordia Fellow" awards (2008 and 1998 respectively), and the "Teaching Excellence Award" given by the Concordia Council of Student Life in 1995.

Prof. Suen has supervised 110 doctoral and master's students to completion, and guided/hosted 90 long-term visiting scientists and professors. He is a fellow of the IEEE (since 1986), IAPR (1994), and the Academy of Sciences of the Royal Society of Canada (1995). Currently, he is the Editor-in-Chief of the journal of Pattern Recognition, an Adviser or Associate Editor of 5 journals, and Editor of a new book series on Language Processing and Pattern Recognition. Actually he has held previous positions as Editor-in-Chief, or Associate Editor or Adviser of 5 other journals. He is not only the founder of three conferences: ICDAR, IWFHR/ICFHR, and VI, but has also organized numerous international conferences including ICPR, ICDAR, ICFHR, ICCPOL, and as Honorary Chair of numerous international conferences. In 1997, he created the IAPR ICDAR Awards, to honour both young and established outstanding researchers in the field of Document Analysis and Recognition.

报告摘要：

Beauty is one of the foremost ideas that define human personality. In this talk, various approaches to the comprehension and analysis of human beauty are presented and the use of these theories is outlined. Each set of theories is translated into a feature model that is tested for classification. Selecting the best set of features that will produce the most accurate model for the representation of the human face is a key challenge. This research combines three main groups of features for the classification of female facial beauty by support vector machines. It concentrates on building an automatic system for the measurement of female facial beauty. Our method analyzes the central tenets of beauty, the successive application image processing techniques, and finally the usage of relevant machine learning methods to build an effective system for automatic assessment and enhancement of facial beauty. Plenty of examples will be illustrated during the talk.

10月20日：卢宏涛：Computer Vision based on Deep Learning

报告题目：Computer Vision based on Deep Learning

报告人：卢宏涛 教授

主持人：孙仕亮 教授

报告时间：10月20号10:00—11：30

报告地点：中北校区理科大楼B1002

报告摘要：

Deep learning has recently achieved great success in many fields such as speech recognition and computer vision, and has so attracted much attention from academic and industry communities. In this talk, I will present some of our recent researches on computer vision based on deep learning. The first is a method for click-through-rate (CTR) prediction in display advertising based on convolutional neural networks. The second is deep learning methods for large scale scene classification. I will also give some examples of deep learning based applications in computer vision such as activity recognition and face detection.

  In addition to deep learning, I will also talk about some other topics such as hashing methods for image retrieval, adaptive affinity matrix for metric learning, a local sparse orthogonal descriptor for image matching etc.

报告人简介：

卢宏涛，现为上海交通大学计算机系教授。研究方向为机器学习、模式识别和计算机视觉。在国内外学术期刊和会议发表论文100多篇。连续入选2014、2015年Elsevier计算机科学中国高被引学榜单。入选2005年教育部新世纪优秀人才计划，2003年上海市曙光学者。获两项省级自然科学和科技进步二等奖。

10月20日：范恩贵：Hermite随机矩阵特征值的分布

报告题目：Hermite随机矩阵特征值的分布

报告人：范恩贵 教授  

所在单位：复旦大学数学科学学院、数学研究所

主持人：陈勇 教授

报告时间：2016年10月20日 14:00-15:30

报告地点：理科大楼B1102

报告摘要：主要介绍Hermite随机矩阵的特征值的各类统计性质： 特征值的独立性，特征值概率密度和关联核的正交多项式刻画，某个区间内特征值的个数， 区间内含有若干个特征值的概率，关联核函数的普适性。

报告人简介：范恩贵，男, 教授、博士生导师。现工作于复旦大学数学科学学院、数学研究所、教育部非线性数学方法与模型开放实验室。研究方向：数学物理、偏微分方程、微分算子谱理论。近年来，连续二届为国家973课题成员、主持国家自然科学基金、上海曙光计划、上海曙光计划跟踪课题等多项研究课题。应邀访问美国密苏里大学、密西根州立大学、德克萨斯大学、波兰华沙大学、香港大学、香港城市大学、日本京都大学等。在《SIAM J Math Phys》、《Math Phys Anal Geom》、《Phys Rev E》、《Stud Appl Math》等国外重要刊物上发表论文80余篇,所发表论文被SCI刊源他引2000余次。2002年，获“上海市曙光学者”称号、2007年，获“上海市自然科学二等奖”、 2008年,获国际“汤姆森路透卓越研究奖” 、 “上海市曙光跟踪学者”称号。

10月20日：丁佐华：Modeling Self-Adaptive Software Systems with Learning Petri Nets

报告题目：Modeling Self-Adaptive Software Systems with Learning Petri Nets

报告人：丁佐华 教授

主持人：刘静 教授

报告时间：10月20日下午13:30-15:00

报告地 点：中北校区数学馆201

报告摘要：Traditional models have limitation to model adaptive software systems since they build only for fixed requirements, and cannot model the behaviors that change at run-time in response to environmental changes. In this paper, an adaptive Petri net is proposed to model a self-adaptive software system. It is an extension of hybrid Petri nets by embedding a neural network algorithm into them at some special transitions. The proposed net has the following advantages:1) It can model a runtime environment; 2) The components in the model can collaborate to make adaption decisions; and 3) The computing is done at the local, while the adaption is for the whole system. We illustrate the proposed adaptive Petri net by modeling a manufacturing system.

报告人简介：

 丁佐华，浙江理工大学信息学院教授，博士生导师，美国南佛罗里达大学(University of South Florida) 数学博士（1998），浙江理工大学《计算机软件与理论》研究所负责人，浙江理工大学信息学院副院长，中国计算机学会软件工程专业委员会委员。主持多项国家自然基金项目，包括一项国际合作重大研究计划项目。在《IEEE Transactions on Service Computing》、《IEEE Transactions on Reliability》、《IEEE Transactions on Fuzzy Systems》、《IEEE Transactions on Systems,Man, and Cybernetics: Systems》《IEEE Transactions on Automation Science and Engineering》、《Journal of Systems and Software》、《中国科学》、ICSE、ICWE、SCC、QSIC、COMPSAC等重要学术刊物和会议上发表学术论文一百多篇。

10月21日：李彪：Breathers and rogue waves in the (2+1)-dimensional nonlinear Schrodinger equation with a parity-time-symmetric potential gomanlb

报告题目：Breathers and rogue waves in the (2+1)-dimensional nonlinear Schrodinger equation with a parity-time-symmetric potential gomanlb

报告人：李彪 教授

所在单位：宁波大学理学院

主持人：陈勇 教授

报告时间：2016年10月21日 14:00-15:00

报告地点：理科大楼B1102          

报告摘要：In this talk, for the (2+1) dimension nonlocal nonlinear Schr¨odinger (NLS) equation with the self-induced parity-time (PT)-symmetric potential is introduced, which provides two-spatial dimensional analogues of the nonlocal nonlinear Schrodinger (NLS) equation introduced by Ablowitz and Musslimani. General periodic solutions are derived by the bilinear method, these periodic solutions behave as growing and decaying periodic line waves arising from the constant background and decaying back to the constant background again. By taking long wave limits of the obtained periodic solutions, rogue waves are obtained. It is also shown that these line rogue waves arise from the constant background with a line profile and disappear into the constant background again in (x; y) plane.

报告人简介：李彪，男，博士，教授。2005年毕业于大连理工大学应用数学系计算数学专业，获理学博士学位。2007年上海交通大学物理系博士后出站。主要从事数学物理，Lie群及其在微分方程中的应用，数学机械化等领域的研究工作。主持完成国家自然科学基金2项，中国博士后基金1项，省自然科学基2项。参与完成国家自然科学基金和省自然科学基金多项。现参加国家自然科学基金重点项目一项，主持国家自然科学基金1项。

10月21日：刘青平：Darboux 变换 --- 从经典到超对称

报告题目：Darboux 变换 --- 从经典到超对称

报告人：刘青平 教授

所在单位：中国矿业大学理学院

主持人：陈勇 教授

报告时间：2016年10月21日 15:00-16:30

报告地点：理科大楼B1102          

报告摘要：Darboux变换是可积系统理论的重要组成部分。在回顾Darboux变换的发展历程的基础上，本报告将围绕典型的超对称可积系统如超对称KdV方程、超对称MKdV方程、超对称NLS方程以及N=2 超对称KdV方程介绍超对称可积系统的Darboux变换的构造和应用。

报告人简介：刘青平， 男，教授，博导。国务院政府特殊津贴获得者，北京市教学名师。现任中国矿业大学（北京）理学院院长。刘青平教授主要从事数学教学和数学物理及非线性科学的分支之一――孤立子理论及其应用研究等工作。1992年10月至1994年10月，在中国科学院理论物理研究所做博士后。1999年，2001年两次访问国际理论物理中心。1997年入选江苏省“333“人才工程。1998年获第八届孙越崎青年科技奖。2000年入选煤炭行业专业技术拔尖人才。2002年入选教育部跨世纪人才计划。