Ch10 Auto-encoders KH Wong Ch10. Auto and variational encoders v.9r6
Ch10. Auto-encoders KH Wong Ch10. Auto and variational encoders v.9r6 1
Two types of autoencoders Part1: Vanilla(traditional) autoencoder or simply called autoencoder Part 2: Variational autoencoder Ch10. Auto and variational encoders v.9r6
Two types of autoencoders • Part1 : Vanilla (traditional) Autoencoder – or simply called Autoencoder • Part 2: Variational Autoencoder Ch10. Auto and variational encoders v.9r6 2
Part 1 Overview of vanilla(traditional) Autoencoder ntroduction Theory Architecture Application Examples Ch10. Auto and variational encoders v.9r6
Part 1: Overview of Vanilla (traditional) Autoencoder • Introduction • Theory • Architecture • Application • Examples Ch10. Auto and variational encoders v.9r6 3
Introduction What is auto-decoder? A unsupervised method Application For noise removal Dimensiona| reductⅰon Method Use noise- free ground truth data(e.g MNIST)+ self generative noise to train the network The final network can remove noise of input corrupted by noise(e.g. hand written characters), the output will be similar to the ground truth data Ch10. Auto and variational encoders v.9r6
Introduction • What is auto-decoder? – A unsupervised method • Application – For noise removal – Dimensional reduction • Method – Use noise-free ground truth data (e.g. MNIST)+ self generative noise to train the network – The final network can remove noise of input corrupted by noise (e.g. hand written characters), the output will be similar to the ground truth data Ch10. Auto and variational encoders v.9r6 4
Noise remova .https://www.slideshare.net/billlangiun/simple-introduction-to-autoencoder 影2 → Encoder Decoder Noisy input Compressed representation Denoised image The feature we want to extract from the image Result: plt title(original images: top rows Z乙(3 Corrupted Input: middle rows Denoised Input: third rows") p乙733 Ch10. Auto and variational encoders v gr6
Noise removal • https://www.slideshare.net/billlangjun/simple-introduction-to-autoencoder Ch10. Auto and variational encoders v.9r6 5 Result: plt.title('Original images: top rows,' 'Corrupted Input: middle rows, ' 'Denoised Input: third rows')