Optical character recognition using transfer learning decision forests

In this paper, we present a novel method for transfer learning which uses decision forests, and we apply it to recognize characters. We introduce two extensions into the decision forest framework in order to transfer knowledge from the source tasks to a given target task. We show that both of them a...

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Detalles Bibliográficos
Autores principales: Goussies, N.A., Ubalde, S., Fernández, F.G., Mejail, M.E.
Formato: CONF
Materias:
decision forests
OCR
transfer learning
Character recognition
Image processing
Learning algorithms
Optical character recognition
Optical data processing
Decision forest
State of the art
Transfer learning
Forestry
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_97814799_v_n_p4309_Goussies
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_97814799_v_n_p4309_Goussies
record_format dspace
spelling todo:paper_97814799_v_n_p4309_Goussies2023-10-03T16:43:39Z Optical character recognition using transfer learning decision forests Goussies, N.A. Ubalde, S. Fernández, F.G. Mejail, M.E. decision forests OCR transfer learning Character recognition Image processing Learning algorithms Optical character recognition Optical data processing Decision forest State of the art Transfer learning Forestry In this paper, we present a novel method for transfer learning which uses decision forests, and we apply it to recognize characters. We introduce two extensions into the decision forest framework in order to transfer knowledge from the source tasks to a given target task. We show that both of them are important to achieve higher recognition rates. Our experiments demonstrate improvements over traditional decision forests in the MNIST dataset. They also compare favorably against other state-of-the-art classifiers. © 2014 IEEE. Fil:Mejail, M.E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. CONF info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_97814799_v_n_p4309_Goussies
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic decision forests
OCR
transfer learning
Character recognition
Image processing
Learning algorithms
Optical character recognition
Optical data processing
Decision forest
State of the art
Transfer learning
Forestry
spellingShingle decision forests
OCR
transfer learning
Character recognition
Image processing
Learning algorithms
Optical character recognition
Optical data processing
Decision forest
State of the art
Transfer learning
Forestry
Goussies, N.A.
Ubalde, S.
Fernández, F.G.
Mejail, M.E.
Optical character recognition using transfer learning decision forests
topic_facet decision forests
OCR
transfer learning
Character recognition
Image processing
Learning algorithms
Optical character recognition
Optical data processing
Decision forest
State of the art
Transfer learning
Forestry
description In this paper, we present a novel method for transfer learning which uses decision forests, and we apply it to recognize characters. We introduce two extensions into the decision forest framework in order to transfer knowledge from the source tasks to a given target task. We show that both of them are important to achieve higher recognition rates. Our experiments demonstrate improvements over traditional decision forests in the MNIST dataset. They also compare favorably against other state-of-the-art classifiers. © 2014 IEEE.
format CONF
author Goussies, N.A.
Ubalde, S.
Fernández, F.G.
Mejail, M.E.
author_facet Goussies, N.A.
Ubalde, S.
Fernández, F.G.
Mejail, M.E.
author_sort Goussies, N.A.
title Optical character recognition using transfer learning decision forests
title_short Optical character recognition using transfer learning decision forests
title_full Optical character recognition using transfer learning decision forests
title_fullStr Optical character recognition using transfer learning decision forests
title_full_unstemmed Optical character recognition using transfer learning decision forests
title_sort optical character recognition using transfer learning decision forests
url http://hdl.handle.net/20.500.12110/paper_97814799_v_n_p4309_Goussies
work_keys_str_mv AT goussiesna opticalcharacterrecognitionusingtransferlearningdecisionforests
AT ubaldes opticalcharacterrecognitionusingtransferlearningdecisionforests
AT fernandezfg opticalcharacterrecognitionusingtransferlearningdecisionforests
AT mejailme opticalcharacterrecognitionusingtransferlearningdecisionforests
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