Optical character recognition systems for different languages with soft computing / Arindam Chaudhuri, Krupa Mandaviya, Pratixa Badelia, Soumya K Ghosh.
Contributor(s): Badelia, Pratixa. | Chaudhuri, Arindam
| Ghosh, Soumya K. | Mandaviya, Krupa.
Material type: 
E-bookSeries: (Studies in fuzziness and soft computing ; volume 352).Publisher: Cham, Switzerland : Springer, 2017Description: 1 recurso en línea.ISBN: 3319502522; 9783319502526.Subject: Inteligencia artificialOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)
Abstract: The book offers a comprehensive survey of soft-computing models for optical character recognition systems. The various techniques, including fuzzy and rough sets, artificial neural networks and genetic algorithms, are tested using real texts written in different languages, such as English, French, German, Latin, Hindi and Gujrati, which have been extracted by publicly available datasets. The simulation studies, which are reported in details here, show that soft-computing based modeling of OCR systems performs consistently better than traditional models. Mainly intended as state-of-the-art survey for postgraduates and researchers in pattern recognition, optical character recognition and soft computing, this book will be useful for professionals in computer vision and image processing alike, dealing with different issues related to optical character recognition.
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | Q342 .O685 2017 EB (Browse shelf(Opens below)) | Acceso electrónico | eBook.20022756 |
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| Q342 .N498 2015 EB New Trends in Computational Collective Intelligence | Q342 .N644 2018 EB Reduction of the Pareto Set An Axiomatic Approach | Q342 .O458 2017 EB Advances and applications of optimised algorithms in image processing | Q342 .O685 2017 EB Optical character recognition systems for different languages with soft computing | Q342 .P477 2018 EB Personal Assistants: Emerging Computational Technologies | Q342 .P763 2016 EB Proceedings of 4th International Conference in Software Engineering for Defence Applications : SEDA 2015 | Q342 .P763 2016 EB Proceedings of the 3rd International Symposium on Big Data and Cloud Computing Challenges (ISBCC � 16�) |
SpringerLink Springer Engineering eBooks 2017 English+International
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The book offers a comprehensive survey of soft-computing models for optical character recognition systems. The various techniques, including fuzzy and rough sets, artificial neural networks and genetic algorithms, are tested using real texts written in different languages, such as English, French, German, Latin, Hindi and Gujrati, which have been extracted by publicly available datasets. The simulation studies, which are reported in details here, show that soft-computing based modeling of OCR systems performs consistently better than traditional models. Mainly intended as state-of-the-art survey for postgraduates and researchers in pattern recognition, optical character recognition and soft computing, this book will be useful for professionals in computer vision and image processing alike, dealing with different issues related to optical character recognition.
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