Multiple classifier fusion in probabilistic neural networks

0410828 - UTIA-B 20020042 RIV GB eng J - Journal Article
Grim, Jiří - Kittler, J. - Pudil, Pavel - Somol, Petr
Multiple classifier fusion in probabilistic neural networks.
Pattern Analysis and Applications. Roč. 5, č. 7 (2002), s. 221-233. ISSN 1433-7541. E-ISSN 1433-755X
R&D Projects: GA ČR GA402/01/0981
Institutional research plan: CEZ:AV0Z1075907
Keywords : EM algorithm * information preserving transform * multiple classifier fusion
Subject RIV: BB - Applied Statistics, Operational Research
Impact factor: 0.667, year: 2002

The main motivation of the present paper is to design a statistically well justified and biologically compatible neural network model and to suggest a theoretical interpretation of the high parallelism of biological neural networks. We consider a probabilistic approach to neural networks in the framework of statistical pattern recognition. The complete method based on EM algorithm has been applied to recognize unconstrained handwritten numerals from the database of the Concordia University Montreal.
Permanent Link: http://hdl.handle.net/11104/0130915