Self-organized learning of 3 dimensions

Cs Szepesvari, A. Lorincz

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

Geometry learning capabilities of a competitive neural network is studied. It is shown, that the appropriate selection of neural activity function enables the learning of the 3 dimensional geometry of a world, from two of 2 dimensional projections of 3 dimensional extended objects.

Original languageEnglish
Pages671-674
Number of pages4
Publication statusPublished - Dec 1 1994
EventProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) - Orlando, FL, USA
Duration: Jun 27 1994Jun 29 1994

Other

OtherProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7)
CityOrlando, FL, USA
Period6/27/946/29/94

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ASJC Scopus subject areas

  • Software

Cite this

Szepesvari, C., & Lorincz, A. (1994). Self-organized learning of 3 dimensions. 671-674. Paper presented at Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7), Orlando, FL, USA, .