An Hybrid MLP-SVM Handwritten Digit Recognizer, - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2001

An Hybrid MLP-SVM Handwritten Digit Recognizer,

Résumé

This paper presents an original hybrid MLP-SVM method for unconstrained handwritten digits recognition. Specialized support vector machines (SVMs) are introduced to improve significantly the multilayer perceptron (MLP) performances in local areas around the separation surfaces between each pair of digit classes, in the input pattern space. This hybrid architecture is based on the idea that the correct digit class almost systematically belongs to the two maximum MLP outputs and that some pairs of digit classes constitute the majority of MLP substitutions (errors). Specialized local SVMs are introduced to detect the correct class among these two classification hypotheses. The hybrid MLP-SVM recognizer achieves a recognition rate of 98.01%, for real mail zip code digits recognition task, a performance better than several classifiers reported in recent researches.
Fichier non déposé

Dates et versions

hal-01571859 , version 1 (03-08-2017)

Identifiants

Citer

Abdel Bellili, Michel Gilloux, Patrick Gallinari. An Hybrid MLP-SVM Handwritten Digit Recognizer,. ICDAR 2001 - 6th International Conference on Document Analysis and Recognition, Sep 2001, Seattle, WA, United States. pp.28-32, ⟨10.1109/ICDAR.2001.953749⟩. ⟨hal-01571859⟩
35 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More