Autoencoders can also be used for image denoising. Denoising is the process of removing noise from the image. A denoising encoder can be trained in an unsupervised manner. The noise can be introduced in a normal image and the autoencoder is trained against the original images. Later, the full autoencoder can be used to produce noise-free images. In this section, we will see step-by-step instructions to denoise MNIST images. Import the required libraries and define the placeholders as shown:
x_input = tf.placeholder(tf.float32, shape=[None, input_size])y_input = tf.placeholder(tf.float32, shape=[None, input_size])
Both x_input and y_input are of the same shape as they should be in an autoencoder. Then, define a ...
