Explainable Artificial Intelligence Xai In Manufacturing

Author : Tin-Chih Toly Chen
Publisher :
ISBN 13 : 9783031279621
Total Pages : 0 pages
Book Rating : 4.2X/5 ( download)

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Download or read book Explainable Artificial Intelligence (XAI) in Manufacturing written by Tin-Chih Toly Chen and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the latest developments in Explainable AI (XAI) and its applications in manufacturing. It covers the various methods, tools, and technologies that are being used to make AI more understandable and communicable for factory workers. With the increasing use of AI in manufacturing, there is a growing need to address the limitations of advanced AI methods that are difficult to understand or explain to those without a background in AI. This book addresses this need by providing a systematic review of the latest research and advancements in XAI specifically tailored for the manufacturing industry. The book includes real-world case studies and examples to illustrate the practical applications of XAI in manufacturing. It is a valuable resource for researchers, engineers, and practitioners working in the field of AI and manufacturing.

Author : Vikas Chaudhary
Publisher : CRC Press
ISBN 13 : 1000504379
Total Pages : 180 pages
Book Rating : 4.78/5 ( download)

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Download or read book Deep Learning in Gaming and Animations written by Vikas Chaudhary and published by CRC Press. This book was released on 2021-12-07 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last decade, progress in deep learning has had a profound and transformational effect on many complex problems, including speech recognition, machine translation, natural language understanding, and computer vision. As a result, computers can now achieve human-competitive performance in a wide range of perception and recognition tasks. Many of these systems are now available to the programmer via a range of so-called cognitive services. More recently, deep reinforcement learning has achieved ground-breaking success in several complex challenges. This book makes an enormous contribution to this beautiful, vibrant area of study: an area that is developing rapidly both in breadth and depth. Deep learning can cope with a broader range of tasks (and perform those tasks to increasing levels of excellence). This book lays a good foundation for the core concepts and principles of deep learning in gaming and animation, walking you through the fundamental ideas with expert ease. This book progresses in a step-by-step manner. It reinforces theory with a full-fledged pedagogy designed to enhance students' understanding and offer them a practical insight into its applications. Also, some chapters introduce and cover novel ideas about how artificial intelligence (AI), deep learning, and machine learning have changed the world in gaming and animation. It gives us the idea that AI can also be applied in gaming, and there are limited textbooks in this area. This book comprehensively addresses all the aspects of AI and deep learning in gaming. Also, each chapter follows a similar structure so that students, teachers, and industry experts can orientate themselves within the text. There are few books in the field of gaming using AI. Deep Learning in Gaming and Animations teaches you how to apply the power of deep learning to build complex reasoning tasks. After being exposed to the foundations of machine and deep learning, you will use Python to build a bot and then teach it the game's rules. This book also focuses on how different technologies have revolutionized gaming and animation with various illustrations.

Author : Tin-Chih Toly Chen
Publisher : Springer Nature
ISBN 13 : 3031279611
Total Pages : 110 pages
Book Rating : 4.14/5 ( download)

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Download or read book Explainable Artificial Intelligence (XAI) in Manufacturing written by Tin-Chih Toly Chen and published by Springer Nature. This book was released on 2023-03-16 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the latest developments in Explainable AI (XAI) and its applications in manufacturing. It covers the various methods, tools, and technologies that are being used to make AI more understandable and communicable for factory workers. With the increasing use of AI in manufacturing, there is a growing need to address the limitations of advanced AI methods that are difficult to understand or explain to those without a background in AI. This book addresses this need by providing a systematic review of the latest research and advancements in XAI specifically tailored for the manufacturing industry. The book includes real-world case studies and examples to illustrate the practical applications of XAI in manufacturing. It is a valuable resource for researchers, engineers, and practitioners working in the field of AI and manufacturing.

Author : Wojciech Samek
Publisher : Springer Nature
ISBN 13 : 3030289540
Total Pages : 435 pages
Book Rating : 4.46/5 ( download)

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Download or read book Explainable AI: Interpreting, Explaining and Visualizing Deep Learning written by Wojciech Samek and published by Springer Nature. This book was released on 2019-09-10 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.

Author : Tin-Chih Toly Chen
Publisher : Springer Nature
ISBN 13 : 303154935X
Total Pages : 113 pages
Book Rating : 4.59/5 ( download)

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Download or read book Explainable Ambient Intelligence (XAmI) written by Tin-Chih Toly Chen and published by Springer Nature. This book was released on with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Denis Rothman
Publisher : Packt Publishing Ltd
ISBN 13 : 1800202768
Total Pages : 455 pages
Book Rating : 4.64/5 ( download)

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Download or read book Hands-On Explainable AI (XAI) with Python written by Denis Rothman and published by Packt Publishing Ltd. This book was released on 2020-07-31 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Resolve the black box models in your AI applications to make them fair, trustworthy, and secure. Familiarize yourself with the basic principles and tools to deploy Explainable AI (XAI) into your apps and reporting interfaces. Key FeaturesLearn explainable AI tools and techniques to process trustworthy AI resultsUnderstand how to detect, handle, and avoid common issues with AI ethics and biasIntegrate fair AI into popular apps and reporting tools to deliver business value using Python and associated toolsBook Description Effectively translating AI insights to business stakeholders requires careful planning, design, and visualization choices. Describing the problem, the model, and the relationships among variables and their findings are often subtle, surprising, and technically complex. Hands-On Explainable AI (XAI) with Python will see you work with specific hands-on machine learning Python projects that are strategically arranged to enhance your grasp on AI results analysis. You will be building models, interpreting results with visualizations, and integrating XAI reporting tools and different applications. You will build XAI solutions in Python, TensorFlow 2, Google Cloud’s XAI platform, Google Colaboratory, and other frameworks to open up the black box of machine learning models. The book will introduce you to several open-source XAI tools for Python that can be used throughout the machine learning project life cycle. You will learn how to explore machine learning model results, review key influencing variables and variable relationships, detect and handle bias and ethics issues, and integrate predictions using Python along with supporting the visualization of machine learning models into user explainable interfaces. By the end of this AI book, you will possess an in-depth understanding of the core concepts of XAI. What you will learnPlan for XAI through the different stages of the machine learning life cycleEstimate the strengths and weaknesses of popular open-source XAI applicationsExamine how to detect and handle bias issues in machine learning dataReview ethics considerations and tools to address common problems in machine learning dataShare XAI design and visualization best practicesIntegrate explainable AI results using Python modelsUse XAI toolkits for Python in machine learning life cycles to solve business problemsWho this book is for This book is not an introduction to Python programming or machine learning concepts. You must have some foundational knowledge and/or experience with machine learning libraries such as scikit-learn to make the most out of this book. Some of the potential readers of this book include: Professionals who already use Python for as data science, machine learning, research, and analysisData analysts and data scientists who want an introduction into explainable AI tools and techniquesAI Project managers who must face the contractual and legal obligations of AI Explainability for the acceptance phase of their applications

Author : Luca Longo
Publisher : Springer Nature
ISBN 13 : 3031440641
Total Pages : 711 pages
Book Rating : 4.49/5 ( download)

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Download or read book Explainable Artificial Intelligence written by Luca Longo and published by Springer Nature. This book was released on 2023-12-05 with total page 711 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume set constitutes the refereed proceedings of the First World Conference on Explainable Artificial Intelligence, xAI 2023, held in Lisbon, Portugal, in July 2023. The 94 papers presented were thoroughly reviewed and selected from the 220 qualified submissions. They are organized in the following topical sections: ​ Part I: Interdisciplinary perspectives, approaches and strategies for xAI; Model-agnostic explanations, methods and techniques for xAI, Causality and Explainable AI; Explainable AI in Finance, cybersecurity, health-care and biomedicine. Part II: Surveys, benchmarks, visual representations and applications for xAI; xAI for decision-making and human-AI collaboration, for Machine Learning on Graphs with Ontologies and Graph Neural Networks; Actionable eXplainable AI, Semantics and explainability, and Explanations for Advice-Giving Systems. Part III: xAI for time series and Natural Language Processing; Human-centered explanations and xAI for Trustworthy and Responsible AI; Explainable and Interpretable AI with Argumentation, Representational Learning and concept extraction for xAI.

Author : Kim Phuc Tran
Publisher : Springer Nature
ISBN 13 : 3031305108
Total Pages : 271 pages
Book Rating : 4.08/5 ( download)

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Download or read book Artificial Intelligence for Smart Manufacturing written by Kim Phuc Tran and published by Springer Nature. This book was released on 2023-06-01 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a comprehensive overview of the latest developments in the field of smart manufacturing, exploring theoretical research, technological advancements, and practical applications of AI approaches. With Industry 4.0 paving the way for intelligent systems and innovative technologies to enhance productivity and quality, the transition to Industry 5.0 has introduced a new concept known as augmented intelligence (AuI), combining artificial intelligence (AI) with human intelligence (HI). As the demand for smart manufacturing continues to grow, this book serves as a valuable resource for professionals and practitioners looking to stay up-to-date with the latest advancements in Industry 5.0. Covering a range of important topics such as product design, predictive maintenance, quality control, digital twin, wearable technology, quantum, and machine learning, the book also features insightful case studies that demonstrate the practical application of these tools in real-world scenarios. Overall, this book provides a comprehensive and up-to-date account of the latest advancements in smart manufacturing, offering readers a valuable resource for navigating the challenges and opportunities presented by Industry 5.0.

Author : Fadi Al-Turjman
Publisher : Elsevier
ISBN 13 : 0323957846
Total Pages : 428 pages
Book Rating : 4.47/5 ( download)

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Download or read book XAI Based Intelligent Systems for Society 5.0 written by Fadi Al-Turjman and published by Elsevier. This book was released on 2023-11-01 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: XAI Based Intelligent Systems for Society 5.0 focuses on the development and analysis of Explainable Artificial Intelligence (XAI)-based models and intelligent systems that can be utilized for Society 5.0—characterized by a knowledge intensive, data driven, and non-monetary society. The book delves into the issues of transparency, explainability, data fusion, and interpretability, which are significant for the development of a super smart society and are addressed through XAI-based models and techniques. XAI-based deep learning models, fuzzy and hybrid intelligent systems, expert systems, and intrinsic explainable models in the context of Society 5.0 are presented in detail. The book also addresses—using XAI-based intelligent techniques—the privacy issues intrinsic in storing huge amounts of data or information in virtual space. The concept of Responsible AI, which is at the core of the future direction of XAI for Society 5.0, is also explored in this book. Finally, the application areas of XAI, including relevant case studies, are presented in the concluding chapter. This book serves as a valuable resource for graduate/post graduate students, academicians, analysts, computer scientists, engineers, researchers, professionals, and other personnel working in the area of artificial intelligence, machine learning, and intelligent systems, who are interested in creating a people-centric smart society. Defines the basic terminology and concepts surrounding explainability and related topics to bring coherence to the field Focuses on what techniques are available to improve explainability and how explainability can progress society Offers a broad range of topics, addressing multiple facets of XAI within the context of Society 5.0

Author : Ajay Kumar
Publisher : CRC Press
ISBN 13 : 1040096956
Total Pages : 376 pages
Book Rating : 4.56/5 ( download)

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Download or read book Handbook of Intelligent and Sustainable Manufacturing written by Ajay Kumar and published by CRC Press. This book was released on 2024-08-28 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent and sustainable manufacturing is a broad category of manufacturing that employs computer-integrated manufacturing, high levels of adaptability and rapid design changes, digital information technology, and more flexible technical workforce training. Other goals sometimes include fast changes in production levels based on demand, optimization of the production system, efficient production, and recyclability. This handbook provides compiled knowledge of intelligent and sustainable manufacturing within the context of Industry 4.0. along with tools, principles, and strategies. Handbook of Intelligent and Sustainable Manufacturing: Tools, Principles, and Strategies offers recent developments, future outlooks, and advanced and analytical modeling techniques of intelligent and sustainable manufacturing with examples backed up by experimental and numerical data. It bridges the gap between R&D in intelligent and sustainable manufacturing–related fields and presents case studies and solutions alongside social and green environmental impact. The handbook includes a wide range of advanced tools and applications with modeling results and explains how different internet technologies integrate the manufacturing approach with people, products, and complex systems. By encompassing advanced technologies such as digital twins, big data informatics, artificial intelligence, nature-inspired algorithms, IoT, Industry 4.0, simulation approaches, analytical strategies, quality tools, roots and pillars, diagnostic tools, and methodical strategies, this handbook provides the most up-to-date and advanced information source available. This handbook will help industries and organizations to implement intelligent manufacturing and move towards the sustainability of manufacturing practices. It will also serve as a reference for senior graduate-level courses in mechanical, production, industrial, and aerospace engineering and a value-added asset to libraries of all technical institutions.