| 當期課號 | 7427 | Course Number | 7427 |
|---|---|---|---|
| 授課教師 | 黃永發 | Instructor | HUANG,YUNG FA |
| 中文課名 | 多媒體資訊系統 | Course Name | Multimedia Information Processing and Classification |
| 開課單位 | 網路與通訊研究所碩士班一A | Department | |
| 修習別 | 選修 | Required/Elective | Elective |
| 學分數 | 3 | Credits | 3 |
| 課程目標 | 使學生學習多媒體系統之基本理論與技術，並瞭解各種媒體之傳輸與壓縮標準。內容包括多媒體介紹，包括文字、影像、圖片、視訊、音效等各種媒體之原理，以及JPEG、MPEG2、MPEG4、JPEG2000等各種標準之原理與技術介紹，並學習一些基礎的編碼壓縮、網路傳輸、與多媒體系統之技術。 | Objectives | Enabling technologies,Computer graphics,Vector graphics,Bitmapped images,Characters and font,Video,Animation,Combining media,Events, scripts and interactivity,Media and networks |
| 教材 | 1.Single and Multi-Carrier DS-CDMA: Multiuser Detection, Space-Time Spreading, Synchronisation, Henzo, Yang, Kuan and Yen, John Wiley & Sons, 2003. | Teaching Materials | 1.Single and Multi-Carrier DS-CDMA: Multiuser Detection, Space-Time Spreading, Synchronisation, Henzo, Yang, Kuan and Yen, John Wiley & Sons, 2003. |
| 成績評量方式 | Midterm 30% Homeworks 30% Final Reports 40% |
Grading | Midterm 30% Homeworks 30% Final Reports 40% |
| 教師網頁 | http://www.cyut.edu.tw/~yfahuang | ||
| 教學內容 | Part 1: Image Processing Chapter 1: Geometric image transforms Chapter 2: Image registration Chapter 3: Image colorization Chapter 4: Image inpainting Chapter 5: Facial image processing Part 2: Image Analysis Chapter 1: Detection of local features Chapter 2: Contour detection Chapter 3: Region segmentation Chapter 4: Content-based image retrieval Chapter 5: Texture analysis Chapter 6: Motion analysis Chapter 7: Camera calibration Chapter 8: Range image acquisition and analysis Chapter 9: Object recognition Part 3: Pattern Recognition Chapter 1: Classification by distance functions Chapter 2: Classification by linear discriminant functions Chapter 3: Nonlinear classifiers: Multilayer neural networks Chapter 4: Classifiers based on Bayesian decision theory Chapter 5: Classification by decision trees Chapter 6: Structural pattern recognition Chapter 7: Syntactic pattern recognition Chapter 8: Multiple classifier systems Chapter 9: Clustering Chapter 10: Hidden Markov Models Chapter 11: Support Vector Machines Chapter 12: Biometrics Part 4: How to write a scientific paper? |
Syllabus | Part 1: Image Processing Chapter 1: Geometric image transforms Chapter 2: Image registration Chapter 3: Image colorization Chapter 4: Image inpainting Chapter 5: Facial image processing Part 2: Image Analysis Chapter 1: Detection of local features Chapter 2: Contour detection Chapter 3: Region segmentation Chapter 4: Content-based image retrieval Chapter 5: Texture analysis Chapter 6: Motion analysis Chapter 7: Camera calibration Chapter 8: Range image acquisition and analysis Chapter 9: Object recognition Part 3: Pattern Recognition Chapter 1: Classification by distance functions Chapter 2: Classification by linear discriminant functions Chapter 3: Nonlinear classifiers: Multilayer neural networks Chapter 4: Classifiers based on Bayesian decision theory Chapter 5: Classification by decision trees Chapter 6: Structural pattern recognition Chapter 7: Syntactic pattern recognition Chapter 8: Multiple classifier systems Chapter 9: Clustering Chapter 10: Hidden Markov Models Chapter 11: Support Vector Machines Chapter 12: Biometrics Part 4: How to write a scientific paper? |