AI Free Basic Course | Lecture 27 | Building AutoEncoder
AI Free Basic Course | Lecture 27 | Building AutoEncoder Look at the image above, it is the image of simple vanilla autoencoder network. Whenever the word Vanilla is used, it means simplest autoencoder. When the image is passed to the encoder it performs two jobs, first it extracts the feature of the image and second is reducing the size of the image. The image is further compressed, and its dimensions are reduced up to code, Bottleneck or Latent representation. It then is passed to the Decoder where the reverse process starts, and the compressed image is expanded, and an image is regenerated. We also discussed in our last lecture the concept of denoising. Where we were giving the input image and were generating another image as an output. Suppose we add noise into our image by drawing lines over it and give it to the autoencoder. Now the burden over the autoencoder has increased. Now it has not only to extract the features of the image but also has to struggle with noise sep...