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

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Springer


Paru le : 2025-09-26

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Description

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.
Pages
424 pages
Collection
n.c
Parution
2025-09-26
Marque
Springer
EAN papier
9783031946363
EAN PDF
9783031946370

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
42
Taille du fichier
16568 Ko
Prix
179,34 €
EAN EPUB
9783031946370

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
42
Taille du fichier
31959 Ko
Prix
179,34 €

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