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Publicado por LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3838306120 ISBN 13: 9783838306124
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Añadir al carritoTaschenbuch. Condición: Neu. Ontology Engineering for Imprecise Knowledge Management | Implementations, Findings and Frameworks | Muhammad Abulaish | Taschenbuch | 224 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783838306124 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
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Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2009
ISBN 10: 3838306120 ISBN 13: 9783838306124
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Añadir al carritoBuch. Condición: Neu. Neuware - Apply revolutionary deep learning technology to the fast-growing field of medical image segmentation.
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Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Jul 2009, 2009
ISBN 10: 3838306120 ISBN 13: 9783838306124
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Currently, knowledge engineering is strongly related to the construction of shared knowledge bases or conceptual frameworks, often designated as ontologies. Ontologies play an active role in the realization of Semantic Web by providing the basis for inter-operability of heterogeneous systems. However, use of ontology in processing information embedded in text documents is still restricted as it is very difficult to predefine an unambiguous and exhaustive ontology for any domain. The context- dependent nature of natural language makes reasoning with text information even more complicated. This book, therefore, provides the theoretical foundations of ontological engineering and covers the practical aspects of ontology learning and enhancement into a fuzzy ontology structure to accommodate uncertainties of natural language. This book can serves as a valuable resource for practicing professionals and applied researchers who are working on building search engines, ontology engineering, text mining, and knowledge-based applications. This book also accommodates the needs of graduate-level students in knowledge engineering and management course. 224 pp. Englisch.
Idioma: Inglés
Publicado por LAP Lambert Academic Publishing, 2009
ISBN 10: 3838306120 ISBN 13: 9783838306124
Librería: moluna, Greven, Alemania
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Currently, knowledge engineering is strongly related to the construction of shared knowledge bases or conceptual frameworks, often designated as ontologies. Ontologies play an active role in the realization of Semantic Web by providing the basis for inter-o.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Jul 2009, 2009
ISBN 10: 3838306120 ISBN 13: 9783838306124
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Currently, knowledge engineering is strongly related to the construction of shared knowledge bases or conceptual frameworks, often designated as ontologies. Ontologies play an active role in the realization of Semantic Web by providing the basis for inter-operability of heterogeneous systems. However, use of ontology in processing information embedded in text documents is still restricted as it is very difficult to predefine an unambiguous and exhaustive ontology for any domain. The context- dependent nature of natural language makes reasoning with text information even more complicated. This book, therefore, provides the theoretical foundations of ontological engineering and covers the practical aspects of ontology learning and enhancement into a fuzzy ontology structure to accommodate uncertainties of natural language. This book can serves as a valuable resource for practicing professionals and applied researchers who are working on building search engines, ontology engineering, text mining, and knowledge-based applications. This book also accommodates the needs of graduate-level students in knowledge engineering and management course.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 224 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2009
ISBN 10: 3838306120 ISBN 13: 9783838306124
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 49,00
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Currently, knowledge engineering is strongly related to the construction of shared knowledge bases or conceptual frameworks, often designated as ontologies. Ontologies play an active role in the realization of Semantic Web by providing the basis for inter-operability of heterogeneous systems. However, use of ontology in processing information embedded in text documents is still restricted as it is very difficult to predefine an unambiguous and exhaustive ontology for any domain. The context- dependent nature of natural language makes reasoning with text information even more complicated. This book, therefore, provides the theoretical foundations of ontological engineering and covers the practical aspects of ontology learning and enhancement into a fuzzy ontology structure to accommodate uncertainties of natural language. This book can serves as a valuable resource for practicing professionals and applied researchers who are working on building search engines, ontology engineering, text mining, and knowledge-based applications. This book also accommodates the needs of graduate-level students in knowledge engineering and management course.
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Añadir al carritoHardcover. Condición: new. Hardcover. Apply revolutionary deep learning technology to the fast-growing field of medical image segmentation Precise medical image segmentation is rapidly becoming one of the most important tools in medical research, diagnosis, and treatment. The potential for deep learning, a technology which is already revolutionizing practice across hundreds of subfields, is immense. The prospect of using deep learning to address the traditional shortcomings of image segmentation demands close inspection and wide proliferation of relevant knowledge. Deep Learning Applications in Medical Image Segmentation meets this demand with a comprehensive introduction and its growing applications. Covering foundational concepts and its advanced techniques, it offers a one-stop resource for researchers and other readers looking for a detailed understanding of the topic. It is deeply engaged with the main challenges and recent advances in the field of deep-learning-based medical image segmentation. Readers will also find: Analysis of deep learning models, including FCN, UNet, SegNet, Dee Lab, and many moreDetailed discussion of medical image segmentation divided by area, incorporating all major organs and organ systemsRecent deep learning advancements in segmenting brain tumors, retinal vessels, and inner ear structuresAnalyzes the effectiveness of deep learning models in segmenting lung fields for respiratory disease diagnosisExplores the application and benefits of Generative Adversarial Networks (GANs) in enhancing medical image segmentationIdentifies and discusses the key challenges faced in medical image segmentation using deep learning techniquesProvides an overview of the latest advancements, applications, and future trends in deep learning for medical image analysis Deep Learning Applications in Medical Image Segmentation is ideal for academics and researchers working with medical image segmentation, as well as professionals in medical imaging, data science, and biomedical engineering. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.