朝陽科技大學 096學年度第1學期教學大綱
Pattern Recognition 圖形識別

當期課號 7454 Course Number 7454
授課教師 戴紹國 Instructor DAI,SHOU KUO
中文課名 圖形識別 Course Name Pattern Recognition
開課單位 資訊科技研究所博士班二A Department  
修習別 選修 Required/Elective Elective
學分數 3 Credits 3
課程目標 1.Classifiers based on Bayes decision theory, 2.Linear/nonlinear classifiers, 3.Feature selection, 4.Feature generation, 5.Context-dependent classification, 6.System evaluation, 7.Clustering algorithms Objectives 1.Classifiers based on Bayes decision theory, 2.Linear/nonlinear classifiers, 3.Feature selection, 4.Feature generation, 5.Context-dependent classification, 6.System evaluation, 7.Clustering algorithms.
教材 Pattern Classification (2nd ed.) by Richard O. Duda, Peter E. Hart and David G. Stork Publisher: Wiley Interscience ISBN: 0-471-05669-3 歐亞書局 Teaching Materials Pattern Classification (2nd ed.) by Richard O. Duda, Peter E. Hart and David G. Stork Publisher: Wiley Interscience ISBN: 0-471-05669-3 歐亞書局
成績評量方式 1.Homework&Quiz: 20%
2.: Midterm: 40%
3.Final Project 40%
Grading 1.Homework&Quiz: 20%
2.Midterm: 40%
3.Final Project 40%
教師網頁  
教學內容 Bayesian decision theory
Parametric estimation and supervised learning
Linear discriminant functions
Nonparametric methods
Feature extraction for representation
Feature extraction for classification
Unsupervised learning and clustering
Syllabus Bayesian decision theory
Parametric estimation and supervised learning
Linear discriminant functions
Nonparametric methods
Feature extraction for representation
Feature extraction for classification
Unsupervised learning and clustering
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