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

Lalitha Krishnasamy

ISBN 10: 3031946367 / ISBN 13: 9783031946363

Published by Springer, Springer Sep 2025, 2025

About this Item

This item is printed on demand - Print on Demand Titel. Neuware Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 432 pp. Englisch.

Seller Inventory # 9783031946363

Bibliographic Details

• Title: Distributed Deep Learning and Explainable AI (XAI) in Industry 4.0
• Publisher: Springer, Springer Sep 2025
• Publication Date: 2025
• Language: English
• ISBN 10: 3031946367
• ISBN 13: 9783031946363
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 28D millimeters 241 millimeters width by 160 millimeters height by 28 millimeters depth
• Weight: 887 grams

About this title

Synopsis

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.