Laboratory image classification using de nwoye ephraim (6 resultados)

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  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2016

    3659949132 / 9783659949135

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    EUR 79,13

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    Cantidad disponible: 1 disponibles

    Paperback. Condición: Brand New. 128 pages. 8.66x5.91x0.29 inches. In Stock.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2016

    3659949132 / 9783659949135

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    EUR 40,20

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    Cantidad disponible: 5 disponibles

    Taschenbuch. Condición: Neu. Laboratory Image Classification using Fuzzy Neural Algorithm: | Application for Colon Cancer Diagnosis | Ephraim Nwoye | Taschenbuch | 128 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659949135 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Sep 2016, 2016

    3659949132 / 9783659949135

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

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    EUR 44,90

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    Cantidad disponible: 2 disponibles

    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Pathologists, daily, screen large numbers of slides containing cancerous cells manually. These are similar in shape, size or cells structure.This procedure or process then becomes arduous, difficult and can affect their judgement and decisions resulting in wrong diagnosis. Therefore development of an automated algorithmic approach, based on quantitative measurements, would be a valuable aid to the pathologist to verify abnormalities. The main aim of this book is therefore to use a neural network approach together with fuzzy arithmetic to establish a relationship between normal and cancer colon cell structures. This relationship is of high significance as it will result in an automated tool for accurate diagnosis. A novel Fast Fuzzy Neural Back-propagation Algorithm (FFNBA) for classification of colon cell images is therefore proposed. The algorithm used an optimal learning method for three layers MLP. The method automatically detects differences in biopsy images of the colorectal polyps, extracts the required image features and then classifies the cells into normal and cancer respectively. 128 pp. Englisch.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2016

    3659949132 / 9783659949135

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    Librería: moluna, Greven, Alemaniamoluna

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    Condición: Nuevo

    EUR 37,98

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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: Nwoye EphraimEphraim Nwoye holds a PhD in Electrical and ElectronicEngineering from the Newcastle University,United Kingdom andcurrently a professor of Biomedical Engineering at the University of Lagos, Nigeria with research interest.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2016

    3659949132 / 9783659949135

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

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    Condición: Nuevo

    EUR 44,90

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    Cantidad disponible: 1 disponibles

    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Pathologists, daily, screen large numbers of slides containing cancerous cells manually. These are similar in shape, size or cells structure.This procedure or process then becomes arduous, difficult and can affect their judgement and decisions resulting in wrong diagnosis. Therefore development of an automated algorithmic approach, based on quantitative measurements, would be a valuable aid to the pathologist to verify abnormalities. The main aim of this book is therefore to use a neural network approach together with fuzzy arithmetic to establish a relationship between normal and cancer colon cell structures. This relationship is of high significance as it will result in an automated tool for accurate diagnosis. A novel Fast Fuzzy Neural Back-propagation Algorithm (FFNBA) for classification of colon cell images is therefore proposed. The algorithm used an optimal learning method for three layers MLP. The method automatically detects differences in biopsy images of the colorectal polyps, extracts the required image features and then classifies the cells into normal and cancer respectively.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Sep 2016, 2016

    3659949132 / 9783659949135

    • Tapa blanda
    • Impresión bajo demanda

    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    Condición: Nuevo

    EUR 44,90

    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 -Pathologists, daily, screen large numbers of slides containing cancerous cells manually. These are similar in shape, size or cells structure.This procedure or process then becomes arduous, difficult and can affect their judgement and decisions resulting in wrong diagnosis. Therefore development of an automated algorithmic approach, based on quantitative measurements, would be a valuable aid to the pathologist to verify abnormalities. The main aim of this book is therefore to use a neural network approach together with fuzzy arithmetic to establish a relationship between normal and cancer colon cell structures. This relationship is of high significance as it will result in an automated tool for accurate diagnosis. A novel Fast Fuzzy Neural Back-propagation Algorithm (FFNBA) for classification of colon cell images is therefore proposed. The algorithm used an optimal learning method for three layers MLP. The method automatically detects differences in biopsy images of the colorectal polyps, extracts the required image features and then classifies the cells into normal and cancer respectively.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 128 pp. Englisch.…