| 當期課號 |
7356 |
Course Number |
7356 |
| 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 |
資訊管理系碩士班二A |
Department |
|
| 修習別 |
選修 |
Required/Elective |
Elective |
| 學分數 |
3 |
Credits |
3 |
| 課程目標 |
圖形識別主要是以一些計量的方法來模擬人類的知覺進行分類，在課程中學生可以了解一些圖形識別的基礎知識，包括，1. Bayes 的分類法, 2. 線性和非線性的分類法, 3. 特徵的選擇和產生, 4. 系統評估和群聚演算法。 |
Objectives |
1.Bayesian decision theory.
2.Parametric estimation and supervised learning.
3.Linear discriminate functions.
4.Nonparametric methods.
5.Feature extraction for representation.
6.Feature extraction for classification.
7.Unsupervised learning and clustering. |
| 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 |
|
| 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 |