This book introduces readers to the field of explainable artificial intelligence (XAI), which aims to make AI models more transparent and trustworthy. It explores how XAI can enhance trust and confidence in AI models and their decisions across various innovative applications in fields such as healthcare, finance, and engineering, where AI can significantly impact quality of life.
Readers will discover emerging trends related to XAI―such as large language models, generative AI, and natural language processing―that are transforming the landscape of AI research and applications. Featuring an interdisciplinary overview, the book examines the state of the art, challenges, and opportunities in XAI, accompanied by clear examples and detailed explanations of its methods and techniques.
The book also offers a balanced perspective on the limitations and trade-offs of XAI and outlines future directions and opportunities for both research and practice. This book is intended for anyone who wants to learn more about XAI and understand how it can enhance trust in AI models.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Nicu Bizon (IEEE M'06; SM'16), was born in Albesti de Muscel, Arges county, Romania, 1961. He received the B.S. degree in electronic engineering from the University "Polytechnic" of Bucharest, Romania, in 1986, and the PhD degree in Automatic Systems and Control from the same university, in 1996. From 1996 to 1989, he was in hardware design with the Dacia Renault SA, Romania. He is currently professor with the National University of Science and Technology POLITEHNICA Bucharest, Pitești University Centre, Romania. He received two awards from Romanian Academy, in 2013 and 2016. He is editor of 17 books and more than 600 papers in scientific fields related to Energy. His current research interests include power electronic converters, fuel cell and electric vehicles, renewable energy, energy storage system, microgrids, and control and optimization of these systems.
Bhargav Appasani received the Ph.D. (Engg.) degree from the Birla Institute of Technology, Mesra, India. He is currently an Associate Professor at the School of Electronics Engineering, KIIT University, Bhubaneswar, India. He has published more than 170 articles in international journals and conference proceedings and has also contributed six book chapters with Springer and Elsevier. Additionally, he has authored four books--two with Springer, one with CRC and one with Nova Science Publishers--and is currently editing two more books, one by CRC Press and the other by Elsevier. He also has four patents filed to his credit. He serves as an academic editor for the Journal of Electrical and Computer Engineering (Wiley) and Applied Computational Intelligence and Soft Computing (Wiley), and Scientific Reports (Springer).
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Hardcover. Etat : new. Hardcover. This book introduces readers to the field of explainable artificial intelligence (XAI), which aims to make AI models more transparent and trustworthy. It explores how XAI can enhance trust and confidence in AI models and their decisions across various innovative applications in fields such as healthcare, finance, and engineering, where AI can significantly impact quality of life. Readers will discover emerging trends related to XAIsuch as large language models, generative AI, and natural language processingthat are transforming the landscape of AI research and applications. Featuring an interdisciplinary overview, the book examines the state of the art, challenges, and opportunities in XAI, accompanied by clear examples and detailed explanations of its methods and techniques. The book also offers a balanced perspective on the limitations and trade-offs of XAI and outlines future directions and opportunities for both research and practice. This book is intended for anyone who wants to learn more about XAI and understand how it can enhance trust in AI models. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9783031970061
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduces readers to the field of explainable artificial intelligence (XAI), which aims to make AI models more transparent and trustworthy. It explores how XAI can enhance trust and confidence in AI models and their decisions across various innovative applications in fields such as healthcare, finance, and engineering, where AI can significantly impact quality of life.Readers will discover emerging trends related to XAI such as large language models, generative AI, and natural language processing that are transforming the landscape of AI research and applications. Featuring an interdisciplinary overview, the book examines the state of the art, challenges, and opportunities in XAI, accompanied by clear examples and detailed explanations of its methods and techniques.The book also offers a balanced perspective on the limitations and trade-offs of XAI and outlines future directions and opportunities for both research and practice. This book is intended for anyone who wants to learn more about XAI and understand how it can enhance trust in AI models. 415 pp. Englisch. N° de réf. du vendeur 9783031970061
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Buch. Etat : Neu. Explainable Artificial Intelligence for Trustworthy Decisions in Smart Applications | Nicu Bizon (u. a.) | Buch | xii | Englisch | 2025 | Springer | EAN 9783031970061 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. N° de réf. du vendeur 134160866
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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book introduces readers to the field of explainable artificial intelligence (XAI), which aims to make AI models more transparent and trustworthy. It explores how XAI can enhance trust and confidence in AI models and their decisions across various innovative applications in fields such as healthcare, finance, and engineering, where AI can significantly impact quality of life.Readers will discover emerging trends related to XAIsuch as large language models, generative AI, and natural language processingthat are transforming the landscape of AI research and applications. Featuring an interdisciplinary overview, the book examines the state of the art, challenges, and opportunities in XAI, accompanied by clear examples and detailed explanations of its methods and techniques.The book also offers a balanced perspective on the limitations and trade-offs of XAI and outlines future directions and opportunities for both research and practice. This book is intended for anyone who wants to learn more about XAI and understand how it can enhance trust in AI models.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 428 pp. Englisch. N° de réf. du vendeur 9783031970061
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces readers to the field of explainable artificial intelligence (XAI), which aims to make AI models more transparent and trustworthy. It explores how XAI can enhance trust and confidence in AI models and their decisions across various innovative applications in fields such as healthcare, finance, and engineering, where AI can significantly impact quality of life.Readers will discover emerging trends related to XAI such as large language models, generative AI, and natural language processing that are transforming the landscape of AI research and applications. Featuring an interdisciplinary overview, the book examines the state of the art, challenges, and opportunities in XAI, accompanied by clear examples and detailed explanations of its methods and techniques.The book also offers a balanced perspective on the limitations and trade-offs of XAI and outlines future directions and opportunities for both research and practice. This book is intended for anyone who wants to learn more about XAI and understand how it can enhance trust in AI models. N° de réf. du vendeur 9783031970061
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Hardcover. Etat : new. Hardcover. This book introduces readers to the field of explainable artificial intelligence (XAI), which aims to make AI models more transparent and trustworthy. It explores how XAI can enhance trust and confidence in AI models and their decisions across various innovative applications in fields such as healthcare, finance, and engineering, where AI can significantly impact quality of life. Readers will discover emerging trends related to XAIsuch as large language models, generative AI, and natural language processingthat are transforming the landscape of AI research and applications. Featuring an interdisciplinary overview, the book examines the state of the art, challenges, and opportunities in XAI, accompanied by clear examples and detailed explanations of its methods and techniques. The book also offers a balanced perspective on the limitations and trade-offs of XAI and outlines future directions and opportunities for both research and practice. This book is intended for anyone who wants to learn more about XAI and understand how it can enhance trust in AI models. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9783031970061
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