Neural Network Approaches to Image Compression

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Image compression with neural networks - A survey (1999, methodology): “While the back-propagation-based narrowchannel neural network aims at achieving a compression upper bounded by the K}L transform, a number of Hebbian learning rules have been developed to address the issue of how the principal components can be directly extracted from input image blocks to achieve i”
Image and Video Compression With Neural Networks: A Review (2019, background): “neurons rather than bringing networks with more layers and complex connections, which may restrict the power of MLP in terms of compression performance [41].”
Deterministic annealing for clustering, compression, classification, regression, and related optimization problems (1998, methodology): “Another approach was to use stochastic gradient techniques [16], particularly in conjunction with self-organizing feature maps, e.g., [22] and [107].”
Comprehensive Review of Artificial Neural Network Applications to Pattern Recognition (2019, background): “The work by Wei et al. [36]; Dony and Haykin [37] focuses on image improvement through image compression.”
Image processing with neural networks - a review (2002, unknown): “For a more extensive overview, see [45].”