De-noising and Contractive are examples of
Answers
The answer is autoencoders.
De-noising and contractive are examples of autoencoders.
A de-noising autoencoder is capable of reconstructing data from an input that consists of corrupted data. An example of corruption would be to remove some parts of the original data. The output of such an encoder is usually a refined version of the original input.
A contractive autoencoder is an unsupervised learning algorithm that is used to train deep networks.
De-noising and contractive are the example of auto-encoder. The auto encoder is actually a network. This type of neural network is responsible to learn or understand the coding of the efficient data that passes over the network in a very efficient manner. A hidden layer is originated over the network that passes the data after encoding them in specific code and then decodes the data into its original form.