Tomovic savo (9 resultados)

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  • Idioma: Inglés

    Editorial: Scholars' Press, 2020

    6138921712 / 9786138921714

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    Librería: Books Puddle, Woodside, NY, Estados Unidos de AmericaBooks Puddle

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    Condición: Nuevo

    EUR 72,85

    Envío por EUR 3,48 
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    Cantidad disponible: 4 disponibles

    Condición: New.

  • Idioma: Inglés

    Editorial: Scholars' Press, 2020

    6138921712 / 9786138921714

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    EUR 78,38

    Envío por EUR 11,66 
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    Cantidad disponible: 1 disponibles

    Paperback. Condición: Brand New. 76 pages. 8.66x5.91x0.18 inches. In Stock.

  • Idioma: Inglés

    Editorial: Scholars' Press, 2020

    6138921712 / 9786138921714

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    Condición: Nuevo

    EUR 41,00

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    Cantidad disponible: 5 disponibles

    Taschenbuch. Condición: Neu. Long life learning system for document understanding | Document understanding in cognitive manner | Savo Tomovic (u. a.) | Taschenbuch | Englisch | 2020 | Scholars' Press | EAN 9786138921714 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

  • Idioma: Inglés

    Editorial: Scholars' Press Jan 2020, 2020

    6138921712 / 9786138921714

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Condición: Nuevo

    EUR 45,90

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -We present long life learning (LLL) system for understanding and processing administrative documents. Special attention was devoted to document classification and information extraction. These two modules represent the most significant part of LLL document understanding system. When changes occur in the document layout or when a novel class of documents appears, the system can adapt to these modifications by running auto-learning procedure. The system does not require a large training data set for creating the initial knowledge. Under specific conditions, it is possible to run the system without preliminary model training. The system will start without knowledge and continuously build and adapt necessary models with each document being processed from the input stream. Platform can process and effectively incorporate feedback from the user into already accumulated knowledge. The proposed solution is comparable to the concurrent systems known from the literature and in some respects even more innovative and appropriate to use in practice. Of course, to achieve accuracy close to a human user much more time, resources and common efforts of all dedicated research groups is needed. 76 pp. Englisch.

  • Idioma: Inglés

    Editorial: Scholars' Press, 2020

    6138921712 / 9786138921714

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    Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books

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    Condición: Nuevo

    EUR 72,08

    Envío por EUR 7,58 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: 4 disponibles

    Condición: New. Print on Demand.

  • Idioma: Inglés

    Editorial: Scholars' Press, 2020

    6138921712 / 9786138921714

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    Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios

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    Condición: Nuevo

    EUR 73,47

    Envío por EUR 9,95 
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    Cantidad disponible: 4 disponibles

    Condición: New. PRINT ON DEMAND.

  • Idioma: Inglés

    Editorial: Scholars\' Press, 2020

    6138921712 / 9786138921714

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    Librería: moluna, Greven, Alemaniamoluna

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    Condición: Nuevo

    EUR 38,74

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    Cantidad disponible: Más de 20 disponibles

    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Tomovic SavoSavo Tomovic received his PhD in computer science from the University of Montenegro. He is currently an associated professor in the Faculty of Science - Department of Mathematics and Computer Science at University of Mont.

  • Idioma: Inglés

    Editorial: Scholars' Press, 2020

    6138921712 / 9786138921714

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Condición: Nuevo

    EUR 66,77

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    Cantidad disponible: 1 disponibles

    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - We present long life learning (LLL) system for understanding and processing administrative documents. Special attention was devoted to document classification and information extraction. These two modules represent the most significant part of LLL document understanding system. When changes occur in the document layout or when a novel class of documents appears, the system can adapt to these modifications by running auto-learning procedure. The system does not require a large training data set for creating the initial knowledge. Under specific conditions, it is possible to run the system without preliminary model training. The system will start without knowledge and continuously build and adapt necessary models with each document being processed from the input stream. Platform can process and effectively incorporate feedback from the user into already accumulated knowledge. The proposed solution is comparable to the concurrent systems known from the literature and in some respects even more innovative and appropriate to use in practice. Of course, to achieve accuracy close to a human user much more time, resources and common efforts of all dedicated research groups is needed.

  • Idioma: Inglés

    Editorial: Scholars' Press Jan 2020, 2020

    6138921712 / 9786138921714

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    Condición: Nuevo

    EUR 45,90

    Envío por EUR 60,00 
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    Cantidad disponible: 1 disponibles

    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -We present long life learning (LLL) system for understanding and processing administrative documents. Special attention was devoted to document classification and information extraction. These two modules represent the most significant part of LLL document understanding system. When changes occur in the document layout or when a novel class of documents appears, the system can adapt to these modifications by running auto-learning procedure. The system does not require a large training data set for creating the initial knowledge. Under specific conditions, it is possible to run the system without preliminary model training. The system will start without knowledge and continuously build and adapt necessary models with each document being processed from the input stream. Platform can process and effectively incorporate feedback from the user into already accumulated knowledge. The proposed solution is comparable to the concurrent systems known from the literature and in some respects even more innovative and appropriate to use in practice. Of course, to achieve accuracy close to a human user much more time, resources and common efforts of all dedicated research groups is needed.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch.