Distributed Deep Learning and Explainable AI (Xai) in Industry 4.0
暫譯: 工業4.0中的分散式深度學習與可解釋的人工智慧 (XAI)
Krishnasamy, Lalitha, Dhanaraj, Rajesh Kumar, Pamucar, Dragan
- 出版商: Springer
- 出版日期: 2025-09-27
- 售價: $7,840
- 貴賓價: 9.5 折 $7,448
- 語言: 英文
- 頁數: 424
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 3031946367
- ISBN-13: 9783031946363
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相關分類:
DeepLearning、Prompt Engineering
海外代購書籍(需單獨結帳)
商品描述
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.
商品描述(中文翻譯)
這本書是一個全面的資源,深入探討先進人工智慧技術在現代工業實踐中的整合。它系統性地探索如何有效地將分散式深度學習方法與可解釋的人工智慧(explainable AI, XAI)結合,以增強工業4.0應用中的透明度。近年來,神經網絡和其他深度學習模型在圖像識別、自然語言處理和決策制定等多個領域產生了顯著的成果。隨著這些模型日益複雜,對其透明度和可解釋性的擔憂也隨之增加。因此,對於與可解釋人工智慧(XAI)相關的方法論和方法的需求也隨之上升。XAI的主要目標是增強深度學習模型決策過程的透明度和可理解性,無論利益相關者的技術專業知識如何。