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Recognition of handwritten numerals by structural probabilistic neural networks
- 1.0410327 - UTIA-B 20000043 RIV CA eng C - Conference Paper (international conference)
Grim, Jiří - Pudil, Pavel - Somol, Petr
Recognition of handwritten numerals by structural probabilistic neural networks.
Wetaskiwin: ICSC, 2000. ISBN 3-906454-22-3. In: Proceedings of the Second ICSC Symposium on Neural Computation. - (Bothe, H.; Rojas, R.), s. 528-534
[NC 2000. Berlin (DE), 23.05.2000-26.05.2000]
R&D Projects: GA ČR GA402/97/1242
Grant - others:GA AV(CZ) IAA2075703; MŠMT(CZ) VS96063
Program: IA
Institutional research plan: AV0Z1075907
Subject RIV: BB - Applied Statistics, Operational Research
http://library.utia.cas.cz/separaty/historie/grim-recognition of handwritten numerals by structural probabilistic neural networks.pdf
The well known "beauty defect" of probabilistic neural networks is the biologically unnatural complete interconnection of neurons. Despite of deep reasons of this undesirable property, it can be removed by a special subspace approach without leaving the exact framework of Bayesian decision-making. The structural optimization based on EM algorithm is controlled by an infor- mation criterion. In the present paper the method has been applied to recognize unconstrained handwritten numerals.
Permanent Link: http://hdl.handle.net/11104/0130418
Number of the records: 1