关于举行台湾元智大学Chih-Min Lin教授和Yung-Sheng Chen教授学术报告会的通知
日期:2012年12月28日 16:42:56

 

报告题目1Development of Cerebellar Model Neural Networks and their Applications on Control, Signal Processing, and Image Classification

  人:Chih-Min Lin教授(台湾元智大学,IEEE 院士)

 

报告题目2A Set of Image Processing Algorithms for Computer-Aided Diagnosis in Nuclear Medicine Whole Body Bone Scan Images

  人:Yung-Sheng Chen教授(台湾元智大学)

 

    间:20121229日上午930

    点:B3-213(大学城)

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                                        计算机科学与工程学院

                                         20121226

报告1内容简介:

Based on biological prototype of human brain and improved understanding of the functionality of the neurons and the pattern of their interconnections in the brain, a theoretical model used to explain the information-processing characteristics of the cerebellum was developed independently by Marr (1969) and Albus (1971). Cerebellar model neural network (CMNN) was first proposed by Albus in 1974. CMNN is a learning structure that imitates the organization and functionality of the cerebellum of the human brain. That model revealed the structure and functionality of the various cells and fibers in the cerebellum. The core of CMNN is an associative memory which has the ability to approach complex nonlinear functions. CMNN takes advantage of the input-redundancy by using distributed storage and can learn nonlinear functions extremely quickly due to the on-line adjustment of its system parameters. CMNN is classified as a non-fully connected perceptron-like associative memory network with overlapping receptive-fields. It has good generalization capability and fast learning property and is suitable for a lot of applications. This speech will introduce several new CMNN-based adaptive learning systems proposed by me; these systems combine the advantages of CMNN identification, adaptive learning, control technique, signal processing and image classification. In these systems, the on-line parameter training methodologies, using the Lyapunov theorem, are proposed to guarantee the stability and convergence of these systems. Moreover, the applications of these systems in nonlinear systems control, biped robot control, signal processing of communication system, and computer-aided diagnosis of breast nodules are demonstrated.

 

报告2内容简介:

Adjustment of brightness and contrast in nuclear medicine whole body bone scan images may confuse nuclear medicine physicians when identifying small bone lesions as well as making the identification of subtle bone lesion changes in sequential studies difficult. In this study, we developed a computer-aided diagnosis system, based on the fuzzy sets histogram thresholding method and anatomical knowledge-based image segmentation method that was able to analyze and quantify raw image data and identify the possible location of a lesion.

 

Chih-Min Lin教授简介:

Prof. Chih-Min Lin is currently a Chair Professor and the Dean of College of Electrical and Communication, Yuan Ze University, Taiwan. He is also an Honorary Professor of Obuda University in Hungary. He also serves as an Associate Editor of IEEE Trans. on Systems, Man, and Cybernetics, Part B; Asian Journal of Control; International Journal of Fuzzy Systems; and International Journal of Machine Learning and Cybernetics. He has been the Chair of IEEE Computational Intelligence Society Taipei Chapter, the Chair of IEEE Systems, Man, and Cybernetics Society Taipei Chapter, a Board of Governor of IEEE Taipei Session. He has gotten the Distinguished Research Award from National Science Council inTaiwanboth in 2008 and 2009. He was also awarded with the Distinguished Engineering Professor from China Engineering Society and the Distinguished Electrical Engineering Professor from Chinese Electrical Engineering Society inTaiwan. He has been invited to give 7 keynote speeches in the international conferences. He is now a Board of Governor of IEEE Systems, Man, and Cybernetics Society. His research interests include fuzzy systems, neural network, cerebellar model neural network, and intelligent control systems. He is an IEEE Fellow and IET Fellow. Till now he has published 125 journal papers and 154 conference papers.

 

Yung-Sheng Chen教授简介:

Prof. Yung-Sheng is currently a Chair Professor and Associate Dean ofCollegeofElectricaland Communication Engineering, Yuan Ze University, Taiwan. He serves as an associate editor of International Journal of Machine Learning and Cybernetics, editorial board member of ISRN Signal Processing. His research interests include 3D image processing, Active visual tracking system, Color image processing, Medical imaging, Fuzzy computing, Image understanding, and Pattern recognition.