Combining Model-based and Discriminative Approaches in a Modular Two-stage Classification System : application to Isolated Handwritten Digit Recognition
Milgram, Jonathan (Université du Québec. École de Technologie Supérieure)
Sabourin, Robert (Université du Québec. École de Technologie Supérieure)
Cheriet, Mohamed (Université du Québec. École de Technologie Supérieure)

Fecha:	2005
Resumen:	The motivation of this work is based on two key observations. First, the classification algorithms can be separated into two main categories: discriminative and model-based approaches. Second, two types of patterns can generate problems: ambiguous patterns and outliers. While, the first approach tries to minimize the first type of error, but cannot deal effectively with outliers, the second approach, which is based on the development of a model for each class, make the outlier detection possible, but are not sufficiently discriminant. Thus, we propose to combine these two different approaches in a modular two-stage classification system embedded in a probabilistic framework. In the first stage we pre-estimate the posterior probabilities with a model-based approach and we re-estimate only the highest probabilities with appropriate Support Vector Classifiers (SVC) in the second stage. Another advantage of this combination is to reduce the principal burden of SVC, the processing time necessary to make a decision and to open the way to use SVC in classification problem with a large number of classes. Finally, the first experiments on the benchmark database MNIST have shown that our dynamic classification process allows to maintain the accuracy of SVCs, while decreasing complexity by a factor 8. 7 and making the outlier rejection available.
Derechos:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Lengua:	Anglès
Documento:	Article ; recerca ; Versió publicada
Materia:	Classifier Combination ; Support Vector Classifier ; Model-based Approach ; Outlier Detection ; Errror-Reject Tradeoff ; Classifying Cost ; Isolated Handwritten Digit Recognition ; Combinació de classificador ; Vectors suport ; Detecció d'outliers ; Costos de classificació ; Reconeixement de dígits manuals aïllats ; Combinación de clasificador ; Vectores soporte ; Detección de outliers ; Costes de clasificación ; Reconocimiento de dígitos manuales aislados
Publicado en:	ELCVIA : Electronic Letters on Computer Vision and Image Analysis, V. 5 n. 2 (2005) p. 1-15, ISSN 1577-5097

Adreça original: https://elcvia.cvc.uab.es/article/view/v5-n2-milgram-sabourin-cheriet
Adreça alternativa: https://raco.cat/index.php/ELCVIA/article/view/31610
DOI: 10.5565/rev/elcvia.92

15 p, 1.3 MB

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