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Image Classification with Growing Neural Networks

Publication at Faculty of Mathematics and Physics |
2013

Abstract

Future multi-media technologies are expected to support on-line processing of huge amounts of high-dimensional data without any special pre-processing. Growing Neural Networks designed for efficient image processing also involve data-dependent adjustment of both the number and position of the neurons that improves generalization.

In this way, local features detected automatically by Growing Neural Networks impact a transparent and compact representation of the extracted knowledge. The performed case studies refer to face and hand-written digit recognition.