| 週次 |
授課內容 |
| 第1週 |
Introduction |
| 第2週 |
Introduction to Neural Networks and Convolutional Neural Networks (I)
NN architecture
Forward/Back propagation
Data-Driven Optimization
Backpropagation Example |
| 第3週 |
放假 |
| 第4週 |
Introduction to Neural Networks and Convolutional Neural Networks (II)
NN architecture
Forward/Back propagation
Data-Driven Optimization
Backpropagation Example |
| 第5週 |
Introduction to Neural Networks and Convolutional Neural Networks (III)
NN architecture
Forward/Back propagation
Data-Driven Optimization
Backpropagation Example |
| 第6週 |
Introduction to Neural Networks and Convolutional Neural Networks
Loss function:
recognition and detection
|
| 第7週 |
CCN-paper (detection&alignmnet)
報告與討論(I)
|
| 第8週 |
CCN-paper (detection&alignmnet)
報告與討論(II) |
| 第9週 |
春假
|
| 第10週 |
Unsupervised Learning- Generative Models (I)
Dimension Reduction- Clustering, K-means, principal components analysis (PCA) |
| 第11週 |
Unsupervised Learning- Generative Models (II)
Generative Adversarial Networks (GAN)
Variational Autoencoders (VAE) |
| 第12週 |
Unsupervised Learning- Generative Models (III)
Generative Adversarial Networks (GAN)
Variational Autoencoders (VAE) |
| 第13週 |
AE-paper 導讀 (I) |
| 第14週 |
AE-paper 報告 (II) |
| 第15週 |
GAN-paper 導讀 (I) |
| 第16週 |
GAN-paper 報告(II) |
| 第17週 |
自主跨域學習 (實作) |
| 第18週 |
自主跨域學習(實作) |