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In den WarenkorbZustand: New. pages cm.
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In den WarenkorbZustand: New. In.
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In den WarenkorbPaperback. Zustand: Brand New. 298 pages. 10.00x7.00x10.00 inches. In Stock.
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In den WarenkorbZustand: New. Dr. Lalitha Krishnasamy received B.Tech IT from CSI College of Engineering, The Nilgris in 2005 and M.Tech IT from Anna University of Technology in 2009 and completed PhD in Wireless Sensor Networks in 2019. Currently working as an Assoc.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.