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商品詳細
Distributed Deep Learning and Explainable AI (XAI) in Industry 4.0.
・ISBN 978-3-031-94636-3 hard EUR 179.99
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| 著者・編者 | Krishnasamy, Lalitha / Dhanaraj, Rajesh Kumar / Pamucar, Dragan / Ouaissa, Mariya (eds.), |
|---|---|
| シリーズ | (Information Systems Engineering and Management) |
| 出版社 | (Springer International Publishing AG, SZ) |
| 出版年月 | 2025 |
| ページ数 | 424 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A04-48550＞ |
解説
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.