| 週次 |
授課內容 |
| 第1週 |
Introduction to deep learning |
| 第2週 |
Machine Learning Basics |
| 第3週 |
Introduction to deep convolutional neural network (filter, kernel, signal processing basics) |
| 第4週 |
Introduction to deep convolutional neural network (classifier-1) |
| 第5週 |
Introduction to deep convolutional neural network (classifier-2) |
| 第6週 |
Autoencoder, Unet, and Segmentation networks |
| 第7週 |
Latent code, Deep feature tensors, and multi-dimensional scaling |
| 第8週 |
Object detection networks |
| 第9週 |
Take-home Midterm or Term Project Proposal |
| 第10週 |
Data Augmentation Methods (1) |
| 第11週 |
Long-tailed Distribution Data Classification |
| 第12週 |
Data Augmentation Methods (2) |
| 第13週 |
Introduction to Generative Adversarial Networks (GANs) |
| 第14週 |
Introduction to Domain Adaptation and Domain Generalization |
| 第15週 |
Introduction to Active Learning |
| 第16週 |
Introduction to Anomaly Detection
Term Project Presentation
Term Project Presentation |
自主學習
內容 |
|