University of Tsukuba | Grad. Scho. Syst. and Info. Eng. | Dept. Comp. Sci. | List of Courses
適応的メディア処理_E
Instructor(s)
Keisuke Kameyama
E-Mail Keisuke.Kameyama@cs.tsukuba.ac.jp
URL http://adapt.cs.tsukuba.ac.jp/moodle263/
Office hours Please contact by mail.
Cource# 01CH609, 01CJ233
Area Media Engineering
Basic/Advanced
Course style Lecture
Term Spring AB
Period Mon2
Room# 3B303
Keywords Signal Processing, Image Processing, Pattern Recognition, Adaptation, Feature Extraction
Prerequisites Basic knowledge on Linear Algebra, Analysis, Probability and Statistics of undergraduate level. Understanding of basic signal processing would be a plus.
Goal
Outline Adaptive techniques in processing, recognition and retrieval of media information will be discussed. (Lecture in English).
Course plan Weeks 1-2
Introduction and reviews on math used in this course.

Weeks 3-7
Theories and techniques for adaptation, recognition and retrieval.
  • Basic Pattern Recognition and the Bayes Rule
  • Linear Discrimination and Adaptive Filters
  • Neural Networks
  • Support Vector Machines
  • Clustering
  • Nearest Neighbor and Subspace Methods

  • Weeks 8-10
    Applications
  • Content-Based Image Retrieval (CBIR)
  • Biometric Authentication
  • Classification of general object images
  • Textbook
    References
  • C. Bishop, Neural networks for pattern recognition, Oxford Univ. Press 1995
  • Haykin, Neural networks - A comprehensive foundation - Prentice Hall 1998
  • F. M. Ham, I. Kostanic, Principles of neurocomputing for science and engineering, McGraw-Hill, 2001
  • C. Bishop, Pattern recognition and machine learning, Springer 2006 (邦訳あり)
  • 熊沢逸夫、学習とニューラルネットワーク、森北出版.
  • Evaluation Irregular small assignments and final term paper will be evaluated.
    TF / TA None
    Misc. Lecture in English
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