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Contributions to the joint segmentation and classification of sequences (My two cents on decoding and handwriting recognition)

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Contributions to the joint segmentation and classification of sequences (My two cents on decoding and handwriting recognition)

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España Boquera, S. (2016). Contributions to the joint segmentation and classification of sequences (My two cents on decoding and handwriting recognition) [Tesis doctoral no publicada]. Universitat Politècnica de València. doi:10.4995/Thesis/10251/62215.

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/62215

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Title: Contributions to the joint segmentation and classification of sequences (My two cents on decoding and handwriting recognition)
Author:
Director(s): Castro Bleda, María José
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Read date / Event date:
2016-01-28
Issued date:
Abstract:
[EN] This work is focused on problems (like automatic speech recognition (ASR) and handwritten text recognition (HTR)) that: 1) can be represented (at least approximately) in terms of one-dimensional sequences, and 2) ...[+]


[ES] Este trabajo se centra en problemas (como reconocimiento automático del habla (ASR) o de escritura manuscrita (HTR)) que cumplen: 1) pueden representarse (quizás aproximadamente) en términos de secuencias unidimensionales, ...[+]


[CAT] Aquest treball es centra en problemes (com el reconeiximent automàtic de la parla (ASR) o de l'escriptura manuscrita (HTR)) on: 1) les dades es poden representar (almenys aproximadament) mitjançant seqüències ...[+]
Subjects: Pattern recognition , Sequence classification , Decoding , Transducer composition , Recurrent Transition Network , Hidden Markov Model , Hybrid HMM , Segment Model , Holistic classifier , Language Modeling , Neural Network Language Model , Handwritten Text Recognition , Slant Correction , Text Size Normalization
Copyrigths: Reserva de todos los derechos
DOI: 10.4995/Thesis/10251/62215
Type: Tesis doctoral

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