Approach to parallel-hierarchical network learning for real-time image sequence recognition

Leonid I. Timchenko; Yuri F. Kutaev; Alexander A. Gertsiy; Lubov V. Zahoruiko; Yaroslav O. Galchenko; Tamer Mansur

doi:10.1117/12.360283

27 August 1999 Approach to parallel-hierarchical network learning for real-time image sequence recognition

Leonid I. Timchenko, Yuri F. Kutaev, Alexander A. Gertsiy, Lubov V. Zahoruiko, Yaroslav O. Galchenko, Tamer Mansur

Proceedings Volume 3836, Machine Vision Systems for Inspection and Metrology VIII; (1999) https://doi.org/10.1117/12.360283
Event: Photonics East '99, 1999, Boston, MA, United States

Abstract

In this work, a new approach for parallel-hierarchical (PH) networks learning having applied to the real-time image sequences in extended laser paths is proposed. It is possible to synthesize PH network with learning abilities by using the general idea of artificial neural networks structured organization on the scheme: input layer - hidden layer - output layer. The 1st network level should be used as input layer, next levels should be used as a hidden layer and the last level should be used as an output one, as it is traditionally in artificial neural networks, Using the main PH network feature which determine the length of network algorithm it is possible to determine a number of hidden layer elements. And in this way it formalizes the procedure of obtaining the number of hidden layer elements.

Citation Download Citation

Leonid I. Timchenko, Yuri F. Kutaev, Alexander A. Gertsiy, Lubov V. Zahoruiko, Yaroslav O. Galchenko, and Tamer Mansur "Approach to parallel-hierarchical network learning for real-time image sequence recognition", Proc. SPIE 3836, Machine Vision Systems for Inspection and Metrology VIII, (27 August 1999); https://doi.org/10.1117/12.360283

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