Overview of Autoencoders
Autoencoders are a type of neural network that can be used to learn a compressed representation of a dataset. They consist of two main parts: an encoder, which maps the input data to a lower-dimensional representation, and a decoder, which maps the lower-dimensional representation back to the original dimensionality. There…
Overview of Autoencoders Autoencoders are a type of neural network that can be used to learn a compressed representation of a dataset. They consist of two main parts: an encoder, which maps the input data to a lower-dimensional representation, and a decoder, which maps the lower-dimensional representation back to the original dimensionality. There… image-processing
Overview Autoencoders Autoencoders type neural network used learn compressed representation dataset consist two main part encoder map input data lowerdimensional representation decoder map lowerdimensional representation back original dimensionality There… imageprocessing