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Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a comprehensive resource that delves into the integration of advanced artificial intelligence techniques within the context of modern industrial practices. It systematically explores how distributed deep learning methodologies can be effectively combined with explainable AI to enhance transparency in Industry 4.0 applications. In recent years, neural networks and other deep learning models have produced remarkable outcomes in a variety of fields, including image recognition, natural language processing, and decision-making. Concerns have been raised regarding the transparency and interpretability of these models as a result of their increasing intricacy. The demand for methodologies and approaches associated with explainable artificial intelligence (XAI) has consequently increased. The primary aim of XAI is to enhance the transparency and comprehensibility of deep learning model decision-making processes for stakeholders, irrespective of their technical expertise.
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Published by Springer, Berlin, Springer Nature Switzerland, Springer, 2025
ISBN 10: 3031946367 ISBN 13: 9783031946363
Language: English
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Add to basketBuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is a comprehensive resource that delves into the integration of advanced artificial intelligence techniques within the context of modern industrial practices. It systematically explores how distributed deep learning methodologies can be effectively combined with explainable AI to enhance transparency in Industry 4.0 applications. In recent years, neural networks and other deep learning models have produced remarkable outcomes in a variety of fields, including image recognition, natural language processing, and decision-making. Concerns have been raised regarding the transparency and interpretability of these models as a result of their increasing intricacy. The demand for methodologies and approaches associated with explainable artificial intelligence (XAI) has consequently increased. The primary aim of XAI is to enhance the transparency and comprehensibility of deep learning model decision-making processes for stakeholders, irrespective of their technical expertise. 424 pp. Englisch.
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Add to basketBuch. Condition: Neu. Distributed Deep Learning and Explainable AI (XAI) in Industry 4.0 | Lalitha Krishnasamy (u. a.) | Buch | vi | Englisch | 2025 | Springer | EAN 9783031946363 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
Published by Springer, Springer Sep 2025, 2025
ISBN 10: 3031946367 ISBN 13: 9783031946363
Language: English
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Add to basketBuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 432 pp. Englisch.