Sinossi
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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Dalla quarta di copertina
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.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Risultati della ricerca per Distributed Deep Learning and Explainable Ai, Xai in...
Foto dell'editore
Distributed Deep Learning and Explainable AI (XAI) in Industry 4.0 (eng)
Print on DemandDa: Brook Bookstore On Demand, Napoli, NA, Italia
Valutazione del venditore 5 su 5 stelle
Condizione: new. Questo è un articolo print on demand. Codice articolo IJAR77TZUH
Compra nuovo
EUR 150,28
EUR 5,50 shipping
Spedito da Italia a U.S.A.
Spedito da Italia a U.S.A.
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Distributed Deep Learning and Explainable AI (XAI) in Industry 4.0
Editore:
Springer, Berlin, Springer Nature Switzerland, Springer, 2025
ISBN 10: 3031946367
ISBN 13: 9783031946363
Nuovo
Rilegato
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Valutazione del venditore 5 su 5 stelle
Buch. Condizione: 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. Codice articolo 9783031946363
Compra nuovo
EUR 192,59
EUR 23,00 shipping
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 2 disponibili
Foto dell'editore
Distributed Deep Learning and Explainable AI (XAI) in Industry 4.0 (Hardcover)
Editore:
Springer International Publishing AG, Cham, 2025
ISBN 10: 3031946367
ISBN 13: 9783031946363
Nuovo
Rilegato
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Valutazione del venditore 5 su 5 stelle
Hardcover. Condizione: new. Hardcover. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9783031946363
Compra nuovo
EUR 222,52
Spedizione gratuita
Spedito in U.S.A.
Spedito in U.S.A.
Quantità: 1 disponibili
Immagini fornite dal venditore
Distributed Deep Learning and Explainable AI (XAI) in Industry 4.0
Print on DemandDa: preigu, Osnabrück, Germania
Valutazione del venditore 5 su 5 stelle
Buch. Condizione: 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. Codice articolo 134146290
Compra nuovo
EUR 168,60
EUR 70,00 shipping
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 5 disponibili
Immagini fornite dal venditore
Distributed Deep Learning and Explainable AI (XAI) in Industry 4.0
Editore:
Springer, Springer Sep 2025, 2025
ISBN 10: 3031946367
ISBN 13: 9783031946363
Nuovo
Rilegato
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Valutazione del venditore 5 su 5 stelle
Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 432 pp. Englisch. Codice articolo 9783031946363
Compra nuovo
EUR 192,59
EUR 60,00 shipping
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 1 disponibili
Immagini fornite dal venditore
Distributed Deep Learning and Explainable AI (XAI) in Industry 4.0
Da: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Buch. Condizione: 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. Codice articolo 9783031946363
Compra nuovo
EUR 192,59
EUR 64,44 shipping
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 1 disponibili
Foto dell'editore
Distributed Deep Learning and Explainable Ai, Xai in Industry 4.0
Editore:
Springer-Nature New York Inc, 2025
ISBN 10: 3031946367
ISBN 13: 9783031946363
Nuovo
Rilegato
Da: Revaluation Books, Exeter, Regno Unito
Valutazione del venditore 5 su 5 stelle
Hardcover. Condizione: Brand New. 430 pages. 9.25x6.10x9.49 inches. In Stock. Codice articolo x-3031946367
Compra nuovo
EUR 273,81
EUR 14,23 shipping
Spedito da Regno Unito a U.S.A.
Spedito da Regno Unito a U.S.A.
Quantità: 1 disponibili