電腦視覺與深度學習
Computer Vision and Deep Learning
| 節 | 週二 |
|---|---|
6 14:20–15:10 | 電腦視覺與深度學習 CM212（歸仁） 3 節連堂 |
7 15:30–16:20 | |
8 16:30–17:20 |
* 根據陽明交大上課時間表所列
The contents of this course discusses the basic concepts and architecture of deep learning and its several vision-based applications including: similarity measure, backpropagation neural networks, convolutional neural networks, recurrent neural networks, feature extraction, face recognition, pedestrian detection, vehicle detection, and so on.
Linear Algebra
無備註
Class lecture, presentation with slides
Homework 20%,General Exam 20%, Mid Exam 30%, Final Exam 30%
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| 週次 | 主題 |
|---|---|
| 第 1 週 | Chapter 1: Introduction 2020/2/18 |
| 第 2 週 | Chapter 2: Applied Math 2020/2/18 2020/2/25 2020/2/25 |
| 第 3 週 | Chapter 3: Probability and Information Theory 2020/3/3 |
| 第 4 週 | Chapter 4: Machine Learning Basics 2020/3/10 |
| 第 5 週 | Chapter 5: Unsupervised and Supervised Learning 2020/3/17 |
| 第 6 週 | Chapter 6: Stochastic Gradient Descent 2020/3/24 |
| 第 7 週 | Chapter 7: Backpropagation Learning 2020/3/31 |
| 第 8 週 | Chapter 8: Regularization and Optimization for Deep Learning 2020/4/7 |
| 第 9 週 | General Exam 2020/4/14 |
| 第 10 週 | Mid Exam 2020/4/21 |
| 第 11 週 | Chapter 9: Deep Convolution Neural Networks 2020/4/28 |
| 第 12 週 | Chapter 10: Sequence Modeling: Recurrent and Recursive Nets 2020/5/5 |
| 第 13 週 | Chapter 11: Face Recognition 2020/5/12 |
| 第 14 週 | Chapter 12: Pedestrian Detection 2020/5/19 |
| 第 15 週 | Chapter 13: Vehicle Analysis 2020/5/26 |
| 第 16 週 | Chapter 13: Vehicle Analysis 2020/6/2 |
| 第 17 週 | overall review 2020/6/9 |
| 第 18 週 | Final Exam 2020/6/16 |
Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville Machine Learning: an algorithm perspective by S. Marsland
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