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ISBN 10: 6205052946 ISBN 13: 9786205052945
Librería: Books Puddle, New York, NY, Estados Unidos de America
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Idioma: Inglés
Publicado por Our Knowledge Publishing, 2022
ISBN 10: 6205052946 ISBN 13: 9786205052945
Librería: moluna, Greven, Alemania
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Idioma: Inglés
Publicado por Our Knowledge Publishing, 2022
ISBN 10: 6205052946 ISBN 13: 9786205052945
Librería: preigu, Osnabrück, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. Machine Learning in Healthcare | An approach for breast cancer detection on histopathological images | Bruno Torres Marques (u. a.) | Taschenbuch | Englisch | 2022 | Our Knowledge Publishing | EAN 9786205052945 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Idioma: Inglés
Publicado por Our Knowledge Publishing Aug 2022, 2022
ISBN 10: 6205052946 ISBN 13: 9786205052945
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 43,90
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Breast cancer is a disease characterized by rampant proliferation of cells that can lead to the appearance of tumors near the breast region. However, the diagnosis of breast cancer has faced several challenges to health professionals and specialists, since it is difficult to analyze biopsy samples, for example. With this in mind and considering the computational advance of computer vision techniques for image recognition, many researchers and experts consider that the use of CAD (Computer-Aided Diagnosis) systems to aid in the diagnosis of breast cancer through the use of image processing and machine learning techniques can contribute positively in the diagnosis of breast cancer among experts. Thus, this work implements three CNN approaches of VGG-16 architecture using the techniques of knowledge transfer and color transfer, aiming to propose and evaluate a solution for the detection of breast cancer in histopathological cancer images using CNN with knowledge transfer and color transfer. 52 pp. Englisch.
Idioma: Inglés
ISBN 10: 6205052946 ISBN 13: 9786205052945
Librería: Majestic Books, Hounslow, Reino Unido
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Idioma: Inglés
Publicado por Our Knowledge Publishing Aug 2022, 2022
ISBN 10: 6205052946 ISBN 13: 9786205052945
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 43,90
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Breast cancer is a disease characterized by rampant proliferation of cells that can lead to the appearance of tumors near the breast region. However, the diagnosis of breast cancer has faced several challenges to health professionals and specialists, since it is difficult to analyze biopsy samples, for example. With this in mind and considering the computational advance of computer vision techniques for image recognition, many researchers and experts consider that the use of CAD (Computer-Aided Diagnosis) systems to aid in the diagnosis of breast cancer through the use of image processing and machine learning techniques can contribute positively in the diagnosis of breast cancer among experts. Thus, this work implements three CNN approaches of VGG-16 architecture using the techniques of knowledge transfer and color transfer, aiming to propose and evaluate a solution for the detection of breast cancer in histopathological cancer images using CNN with knowledge transfer and color transfer.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 44,59
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Breast cancer is a disease characterized by rampant proliferation of cells that can lead to the appearance of tumors near the breast region. However, the diagnosis of breast cancer has faced several challenges to health professionals and specialists, since it is difficult to analyze biopsy samples, for example. With this in mind and considering the computational advance of computer vision techniques for image recognition, many researchers and experts consider that the use of CAD (Computer-Aided Diagnosis) systems to aid in the diagnosis of breast cancer through the use of image processing and machine learning techniques can contribute positively in the diagnosis of breast cancer among experts. Thus, this work implements three CNN approaches of VGG-16 architecture using the techniques of knowledge transfer and color transfer, aiming to propose and evaluate a solution for the detection of breast cancer in histopathological cancer images using CNN with knowledge transfer and color transfer.