Fr. 215.00

Distributed Deep Learning and Explainable AI (XAI) in Industry 4.0

Inglese · Copertina rigida

Pubblicazione il 10.08.2025

Descrizione

Ulteriori informazioni

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.

Sommario

Introduction to Industry 4.0: Practical issues and challenges.- Explainable AI Principles for Industry 4.0.- Explainable AI principles of building industry 4.0.- Transformative Healthcare: Industry 4.0 Integration of Distributed Deep Learning and XAI.

Dettagli sul prodotto

Con la collaborazione di Rajesh Kumar Dhanaraj (Editore), Lalitha Krishnasamy (Editore), Rajesh Kumar Dhanaraj (Editore), Mariya Ouaissa (Editore), Dragan Pamucar (Editore), Dragan Pamucar et al (Editore)
Editore Springer, Berlin
 
Lingue Inglese
Formato Copertina rigida
Pubblicazione 10.08.2025
 
EAN 9783031946363
ISBN 978-3-0-3194636-3
Pagine 382
Illustrazioni XII, 382 p. 167 illus., 159 illus. in color.
Serie Information Systems Engineering and Management
Categorie Scienze naturali, medicina, informatica, tecnica > Tecnica > Tematiche generali, enciclopedie

Datenbanken, Artificial Intelligence, Deep Learning, Predictive Maintenance, Industry 4.0, quality control, Data Engineering, Computational Intelligence, Smart Manufacturing, human-robot collaboration, AI Technologies, Grad-CAM, Robotics Automation, AI Frameworks, Emerging Tools, Adaptive Decision-making

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