Processing of noisy digital images with use of evolving autoencoders
Journal: Eastern-European Journal of Enterprise Technologies
Year: 2017

A promising class of neural network models used recently to solve the problems of recognition of noisy images are denoising autoencoders. In particular, the evolutionary approach can be effectively used in DAE to determine the network architecture, weights and learning algorithm. The proposed neural network evolving autoencoder allows efficient processing of noisy images due to the iterative learning procedure even in the presence of local distortions. When using the EDAE for determining the net