Course title
パターン認識と機械学習   [Pattern Recognition and Machine Learning]
Course category technology speciality courses  Requirement   Credit 2 
Department   Year 34  Semester 1st 
Course type 1st  Course code 023662
Instructor(s)
堀田 政二   [HOTTA Seiji]
Facility affiliation Faculty of Engineering Office afjgxte/L1151  Email address

Course description
Pattern recognition classifies, identifies or recognizes symbols, structures or any type of information represented, conveyed or even hidden in a set of signals which are redundant and often noisy. It is theoretically and scientifically important to learn human abilities of pattern recognition and practically important to realize smooth human machine interaction.
Expected Learning
Refer to the curriculum polices shown in the TUAT web site.
Course schedule
1. What are patterns, what is pattern recognition?
2. Human Pattern Recognition, Findings from Pathology, Neurophysiology and Cognitive Science
3. Pattern Recognition by Computers
4. Discriminant Functions
5. Introduction to Statistical Methods
6. Details in Statistical Methods (quadratic discriminant function, and modified quadratic discriminant function)
7. Clustering and Prototype Learning
8. Neural Networks
9. Convolutional NN and Recurrent NN
10. Elastic Matching
11. Practical Issues (Normalization, Feature extraction, Feature selection)
12. Practice of Handwritten Character Recognition
13. Structural Methods and Typical Examples
14. Context Processing
15. Summary and examination
Prerequisites
Mathematics
In addition to 30 hours that students spend in the class, students are recommended to prepare for and revise the lectures, spending the standard amount of time as specified by the University and using the lecture handouts as well as the references specified below
Required Text(s) and Materials
References
Duda, Hart, Stork: Pattern Classification, John Wiley & Sons.
Assessment/Grading
Participation 30%, Essays twice 10% and Examination 60%
Message from instructor(s)
Course keywords
Office hours
Remarks 1
Remarks 2
Related URL
Lecture Language
Language Subject
Last update
3/3/2021 10:29:36 AM