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General Information
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2013 Vol.5(3): 422-427 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2013.V5.722

Image Classification with Growing Neural Networks

Iveta Mrazova and Marek Kukacka
Abstract—Future multi-media technologies are expected to support efficient on-line processing of huge amounts of high-dimensional data without any special pre-processing. In this paper, we will introduce a new model of the so-called Growing Hierarchical Neural Networks (GHNN) applicable to image classification without requiring advanced domain-specific feature extraction techniques. It can be, moreover, supposed that the involved dynamic data-dependent adjustment of both the number and position of the neurons improves generalization. Experimental results obtained so far for two case studies on face and hand-written digit recognition show that local features detected automatically by GHNN-networks impact a transparent and compact representation of the extracted knowledge.

Index Terms—Convolutional neural networks, image classification, face recognition, self-organization.

The authors are with the Department of Theoretical Computer Science and Mathematical Logic, Faculty of Mathematics and Physics, Charles University, Malostranske nam. 25, 118 00 Praha, Czech Republic (e-mail: iveta.mrazova@mff.cuni.cz, mkukacka@gmail.com).


Cite:Iveta Mrazova and Marek Kukacka, "Image Classification with Growing Neural Networks," International Journal of Computer Theory and Engineering vol. 5, no. 3, pp. 422-427, 2013.

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