朝陽科技大學 095學年度第1學期教學大綱
Pattern Recognition 圖形識別

當期課號 7386 Course Number 7386
授課教師 吳世弘 Instructor WU,SHIH HUNG
中文課名 圖形識別 Course Name Pattern Recognition
開課單位 資訊工程系碩士班一A Department  
修習別 選修 Required/Elective Elective
學分數 3 Credits 3
課程目標 本課程主要介紹圖形識別的知識,學生在本課程將可了解相關概念有:貝氏定理分類器,線性與非線性分類器,特徵挑選,特徵產生,脈絡相關分類,系統評估,分群演算法 Objectives The goal of this course is to provide the students with a basic knowledge of pattern recognition. The students will realize the following concepts in the course:
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 1. Pattern Classification (2nd ed.)
by Richard O. Duda, Peter E. Hart and David G. Stork
Wiley Interscience
680 pages
ISBN: 0-471-05669-3
歐亞書局

2. Pattern Recognition (2nd ed.)
by Theodoridis and Koutroumbas.
Academic Press
全華圖書
Teaching Materials 1. Pattern Classification (2nd ed.)
by Richard O. Duda, Peter E. Hart and David G. Stork
Wiley Interscience
680 pages
ISBN: 0-471-05669-3
歐亞書局

2. Pattern Recognition (2nd ed.)
by Theodoridis and Koutroumbas.
Academic Press
全華圖書
成績評量方式 1.Presentation:50%
2.Project Report:30%
3.Q&A:20%
Grading 1.Presentation:50%
2.Project report:30%
3.Q&A:20%
教師網頁 http://www.csie.cyut.edu.tw/~shwu
教學內容 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 Syllabus 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
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