圖形識別
Pattern Recognition
| 節 | 週四 |
|---|---|
2 09:00–09:50 | 圖形識別 EE208 3 節連堂 |
3 10:10–11:00 | |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
Machine intelligence will be a dominant technology in the 21 century. Pattern Recognition techniques are an important component of intelligent systems and are used for both data preprocessing and decision making. Generally speaking, pattern recognition is the science that concerns the description or classification of measurement. Since no single technology is always the optimum solution for a given pattern recognition problem, the statistical pattern recognition and neural pattern recognition are explored in this course.
微積分
1. 第一週上課日會宣布本課程的相關注意事項,同時也會公布在E3教學平台。 2. 本課程為網路教學:從第二週開始,每週在E3教學平台播放3段教學影片。 3. 上課內容可以在 EE731 找到。 4. 加簽辦法: a.可以網路選課者,歡迎使用網路加選或候補加選本課程; b.需紙本加簽者,在不超過修課人數上限的前提下,從2月20日早上9點起在工五館770室辦理。
期中考:40% 期末考 : 60 %
- Introduction
- Decision - Theoretic Algorithms
- Statistical Classification
- Feature Selection
- Fuzzy Classification
- Neural Network Approach
- Neural Network and Classification
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction |
| 第 2 週 | Decision - Theoretic Algorithms (1) |
| 第 3 週 | Decision - Theoretic Algorithms (2) |
| 第 4 週 | Decision - Theoretic Algorithms (3) |
| 第 5 週 | Statistical Classification (1) |
| 第 6 週 | Statistical Classification (2) |
| 第 7 週 | Statistical Classification (3) |
| 第 8 週 | Statistical Classification (4) |
| 第 9 週 | Feature Selection (1) |
| 第 10 週 | Feature Selection (2) |
| 第 11 週 | Feature Selection (3) |
| 第 12 週 | Fuzzy Classification (1) |
| 第 13 週 | Fuzzy Classification (2) |
| 第 14 週 | Fuzzy Approach |
| 第 15 週 | Neural Network Approach (1) |
| 第 16 週 | Neural Network Approach (2) |
| 第 17 週 | Neural Network and Classification (1) |
| 第 18 週 | Neural Network and Classification (2) |
無 以下所列書籍僅為參考書籍並非教科書 (1) M. Frieddman and A. Kandel, Introduction to Pattern Recognition, World Scientific, 1999. (2) 林昇甫, 洪成安, 神經網路入門與圖樣辨識, 修訂二版, 全華圖書, 2002.
- 地點
- EE770
- 時間
- 每週四9:00至12:00
- 聯絡方式
- e-mail or 分機 54365