Detection of ambiguous patterns in a SOM based recognition system: Application to handwritten numeral classification

This work presents a system for pattern recognition that combines a self-organising unsupervised technique (via a Kohonen-type SOM) with a bayesian strategy in order to classify input patterns from a given probability distribution and, at the same time, detect ambiguous cases and explain answers. We...

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Detalles Bibliográficos
Autores principales: Seijas, L.M., Segura, E.C., Universitat Bielefeld; SFB 673
Formato: CONF
Materias:
Bayesian statistics
Pattern recognition
Self-organising maps
Ambiguous patterns
Concordia University
Handwritten digit
Handwritten numeral
Recognition systems
Self-organising
Unsupervised techniques
Conformal mapping
Probability distributions
Self organizing maps
Pattern recognition systems
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_NIS12828_v_n_p_Seijas
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

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