Chinese Handwriting Recognition: An Algorithmic Perspective

This book provides an algorithmic perspective on the recent development of Chinese handwriting recognition. Two technically sound strategies, the segmentation-free and integrated segmentation-recognition strategy, are investigated and algorithms that have worked well in practice are primarily focuse...

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Detalles Bibliográficos
Autor Principal: Su, Tonghua
Formato: Livre numérique
Idioma:Anglais
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg 2013.
Cham : Springer Nature
Series:SpringerBriefs in Electrical and Computer Engineering
Acceso en liña:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Nota: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Chinese Handwriting Recognition: An Algorithmic Perspective, Texte imprimé, 9783642318115
• Chinese Handwriting Recognition: An Algorithmic Perspective, Texte imprimé, 9783642318139
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505 0 |a Introduction -- HIT-MW Database -- Integrated Segmentation-Recognition Strategy -- Segmentation-free Strategy: Basic Algorithms -- Segmentation-free Strategy: Advanced Algorithms. 
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520 |a This book provides an algorithmic perspective on the recent development of Chinese handwriting recognition. Two technically sound strategies, the segmentation-free and integrated segmentation-recognition strategy, are investigated and algorithms that have worked well in practice are primarily focused on. Baseline systems are initially presented for these strategies and are subsequently expanded on and incrementally improved. The sophisticated algorithms covered include: 1) string sample expansion algorithms which synthesize string samples from isolated characters or distort realistic string samples; 2) enhanced feature representation algorithms, e.g. enhanced four-plane features and Delta features; 3) novel learning algorithms, such as Perceptron learning with dynamic margin, MPE training and distributed training; and lastly 4) ensemble algorithms, that is, combining the two strategies using both parallel structure and serial structure. All the while, the book moves from basic to advanced algorithms, helping readers quickly embark on the study of Chinese handwriting recognition. 
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