Author: Fadi Al-Turjman
Publisher: Elsevier
ISBN: 0323957846
Category : Political Science
Languages : en
Pages : 428
Book Description
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
XAI Based Intelligent Systems for Society 5.0
Author: Fadi Al-Turjman
Publisher: Elsevier
ISBN: 0323957846
Category : Political Science
Languages : en
Pages : 428
Book Description
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
Publisher: Elsevier
ISBN: 0323957846
Category : Political Science
Languages : en
Pages : 428
Book Description
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
Explainable AI in Healthcare
Author: Mehul S Raval
Publisher: CRC Press
ISBN: 100090640X
Category : Medical
Languages : en
Pages : 346
Book Description
This book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electrical engineering. This book will benefit readers in the following ways: Explores state of art in computer vision and deep learning in tandem to develop autonomous or semi-autonomous algorithms for diagnosis in health care Investigates bridges between computer scientists and physicians being built with XAI Focuses on how data analysis provides the rationale to deal with the challenges of healthcare and making decision-making more transparent Initiates discussions on human-AI relationships in health care Unites learning for privacy preservation in health care
Publisher: CRC Press
ISBN: 100090640X
Category : Medical
Languages : en
Pages : 346
Book Description
This book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electrical engineering. This book will benefit readers in the following ways: Explores state of art in computer vision and deep learning in tandem to develop autonomous or semi-autonomous algorithms for diagnosis in health care Investigates bridges between computer scientists and physicians being built with XAI Focuses on how data analysis provides the rationale to deal with the challenges of healthcare and making decision-making more transparent Initiates discussions on human-AI relationships in health care Unites learning for privacy preservation in health care
Producing Artificial Intelligent Systems
Author: Maria Isabel Aldinhas Ferreira
Publisher: Springer Nature
ISBN: 3031558170
Category :
Languages : en
Pages : 173
Book Description
Publisher: Springer Nature
ISBN: 3031558170
Category :
Languages : en
Pages : 173
Book Description
Design Science Research for a New Society: Society 5.0
Author: Aurona Gerber
Publisher: Springer Nature
ISBN: 3031328086
Category : Computers
Languages : en
Pages : 491
Book Description
This book constitutes the proceedings of the 18th International Conference on Design Science Research in Information Systems and Technology, DESRIST 2023, which was held in Pretoria, South Africa, from May 31–June 2, 2023. The 29 full papers presented in this volume were carefully reviewed and selected from 81 submissions. The papers are organized in the following topical sections: Design-oriented Research for Society 5.0 (Theme Track); Design of Systems Using Emerging Technologies; Human-Centered Artificial Intelligence (HCAI); Healthcare Systems and Quality of Life; Innovation and Entrepreneurship; Emerging DSR Methods and Processes; Education and DRS; Human Safety and Cybersecurity; Co-Desing and Collective Creativity for Addressing Grand Challenges; and Sustainability and Responsible Design.
Publisher: Springer Nature
ISBN: 3031328086
Category : Computers
Languages : en
Pages : 491
Book Description
This book constitutes the proceedings of the 18th International Conference on Design Science Research in Information Systems and Technology, DESRIST 2023, which was held in Pretoria, South Africa, from May 31–June 2, 2023. The 29 full papers presented in this volume were carefully reviewed and selected from 81 submissions. The papers are organized in the following topical sections: Design-oriented Research for Society 5.0 (Theme Track); Design of Systems Using Emerging Technologies; Human-Centered Artificial Intelligence (HCAI); Healthcare Systems and Quality of Life; Innovation and Entrepreneurship; Emerging DSR Methods and Processes; Education and DRS; Human Safety and Cybersecurity; Co-Desing and Collective Creativity for Addressing Grand Challenges; and Sustainability and Responsible Design.
Handbook of Research on Network-Enabled IoT Applications for Smart City Services
Author: Reddy, K. Hemant Kumar
Publisher: IGI Global
ISBN:
Category : Political Science
Languages : en
Pages : 437
Book Description
The rapid growth of IoT and its applications in smart cities pose significant challenges for academic scholars. The increasing number of interconnected devices and the massive amounts of data they generate strain traditional networks, leading to inefficiencies and security vulnerabilities. Additionally, the centralized control plane in Software Defined Networks (SDN) presents a single point of failure, hindering network performance, while IoT devices themselves are susceptible to attacks, compromising user data and privacy. To address these pressing issues, Network-Enabled IoT Applications for Smart City Services offers a compelling solution. Edited by Dr. K. Hemant Kumar Reddy, Dr. Diptendu SinhaRoy, and Tapas Mishra, this book advocates leveraging SDN to handle high-frequency data streams effectively. It also proposes the integration of blockchain technology to enhance security and reliability in IoT applications, offering a roadmap for scholars to improve network efficiency, security, and reliability in IoT and smart city domains. With their extensive expertise, the authors provide academic scholars with a comprehensive and innovative resource that inspires further research and development in this evolving field, enabling them to make significant contributions to the advancement of IoT and smart city technologies.
Publisher: IGI Global
ISBN:
Category : Political Science
Languages : en
Pages : 437
Book Description
The rapid growth of IoT and its applications in smart cities pose significant challenges for academic scholars. The increasing number of interconnected devices and the massive amounts of data they generate strain traditional networks, leading to inefficiencies and security vulnerabilities. Additionally, the centralized control plane in Software Defined Networks (SDN) presents a single point of failure, hindering network performance, while IoT devices themselves are susceptible to attacks, compromising user data and privacy. To address these pressing issues, Network-Enabled IoT Applications for Smart City Services offers a compelling solution. Edited by Dr. K. Hemant Kumar Reddy, Dr. Diptendu SinhaRoy, and Tapas Mishra, this book advocates leveraging SDN to handle high-frequency data streams effectively. It also proposes the integration of blockchain technology to enhance security and reliability in IoT applications, offering a roadmap for scholars to improve network efficiency, security, and reliability in IoT and smart city domains. With their extensive expertise, the authors provide academic scholars with a comprehensive and innovative resource that inspires further research and development in this evolving field, enabling them to make significant contributions to the advancement of IoT and smart city technologies.
Explainable Ambient Intelligence (XAmI)
Author: Tin-Chih Toly Chen
Publisher: Springer Nature
ISBN: 303154935X
Category :
Languages : en
Pages : 113
Book Description
Publisher: Springer Nature
ISBN: 303154935X
Category :
Languages : en
Pages : 113
Book Description
Artificial Intelligence and Machine Learning for Smart Community
Author: T V Ramana
Publisher: CRC Press
ISBN: 1003835724
Category : Computers
Languages : en
Pages : 148
Book Description
Intelligent systems are technologically advanced machines that perceive and respond to the world around them. Artificial Intelligence and Machine Learning for Smart Community: Concepts and Applications presents the evolution, challenges, and limitations of the application of machine learning and artificial intelligence to intelligent systems and smart communities. Covers the core and fundamental aspects of artificial intelligence, machine learning, and computational algorithms in smart intelligent systems Discusses the integration of artificial intelligence with machine learning using mathematical modeling Elaborates concepts like supervised and unsupervised learning, and machine learning algorithms, such as linear regression, logistic regression, random forest, and performance evaluation matrices Introduces modern algorithms such as convolutional neural networks and support vector machines Presents case studies on smart healthcare, smart traffic management, smart buildings, autonomous vehicles, smart education, modern community, and smart machines Artificial Intelligence and Machine Learning for Smart Community: Concepts and Applications is primarily written for graduate students and academic researchers working in the fields of computer science and engineering, electrical engineering, and information technology. Seasonal Blurb: This reference text presents the most recent and advanced research on the application of artificial intelligence and machine learning on intelligent systems. It will discuss important topics such as business intelligence, reinforcement learning, supervised learning, and unsupervised learning in a comprehensive manner.
Publisher: CRC Press
ISBN: 1003835724
Category : Computers
Languages : en
Pages : 148
Book Description
Intelligent systems are technologically advanced machines that perceive and respond to the world around them. Artificial Intelligence and Machine Learning for Smart Community: Concepts and Applications presents the evolution, challenges, and limitations of the application of machine learning and artificial intelligence to intelligent systems and smart communities. Covers the core and fundamental aspects of artificial intelligence, machine learning, and computational algorithms in smart intelligent systems Discusses the integration of artificial intelligence with machine learning using mathematical modeling Elaborates concepts like supervised and unsupervised learning, and machine learning algorithms, such as linear regression, logistic regression, random forest, and performance evaluation matrices Introduces modern algorithms such as convolutional neural networks and support vector machines Presents case studies on smart healthcare, smart traffic management, smart buildings, autonomous vehicles, smart education, modern community, and smart machines Artificial Intelligence and Machine Learning for Smart Community: Concepts and Applications is primarily written for graduate students and academic researchers working in the fields of computer science and engineering, electrical engineering, and information technology. Seasonal Blurb: This reference text presents the most recent and advanced research on the application of artificial intelligence and machine learning on intelligent systems. It will discuss important topics such as business intelligence, reinforcement learning, supervised learning, and unsupervised learning in a comprehensive manner.
Practical Explainable AI Using Python
Author: Pradeepta Mishra
Publisher: Apress
ISBN: 9781484271575
Category : Computers
Languages : en
Pages : 344
Book Description
Learn the ins and outs of decisions, biases, and reliability of AI algorithms and how to make sense of these predictions. This book explores the so-called black-box models to boost the adaptability, interpretability, and explainability of the decisions made by AI algorithms using frameworks such as Python XAI libraries, TensorFlow 2.0+, Keras, and custom frameworks using Python wrappers. You'll begin with an introduction to model explainability and interpretability basics, ethical consideration, and biases in predictions generated by AI models. Next, you'll look at methods and systems to interpret linear, non-linear, and time-series models used in AI. The book will also cover topics ranging from interpreting to understanding how an AI algorithm makes a decision Further, you will learn the most complex ensemble models, explainability, and interpretability using frameworks such as Lime, SHAP, Skater, ELI5, etc. Moving forward, you will be introduced to model explainability for unstructured data, classification problems, and natural language processing–related tasks. Additionally, the book looks at counterfactual explanations for AI models. Practical Explainable AI Using Python shines the light on deep learning models, rule-based expert systems, and computer vision tasks using various XAI frameworks. What You'll Learn Review the different ways of making an AI model interpretable and explainable Examine the biasness and good ethical practices of AI models Quantify, visualize, and estimate reliability of AI models Design frameworks to unbox the black-box models Assess the fairness of AI models Understand the building blocks of trust in AI models Increase the level of AI adoption Who This Book Is For AI engineers, data scientists, and software developers involved in driving AI projects/ AI products.
Publisher: Apress
ISBN: 9781484271575
Category : Computers
Languages : en
Pages : 344
Book Description
Learn the ins and outs of decisions, biases, and reliability of AI algorithms and how to make sense of these predictions. This book explores the so-called black-box models to boost the adaptability, interpretability, and explainability of the decisions made by AI algorithms using frameworks such as Python XAI libraries, TensorFlow 2.0+, Keras, and custom frameworks using Python wrappers. You'll begin with an introduction to model explainability and interpretability basics, ethical consideration, and biases in predictions generated by AI models. Next, you'll look at methods and systems to interpret linear, non-linear, and time-series models used in AI. The book will also cover topics ranging from interpreting to understanding how an AI algorithm makes a decision Further, you will learn the most complex ensemble models, explainability, and interpretability using frameworks such as Lime, SHAP, Skater, ELI5, etc. Moving forward, you will be introduced to model explainability for unstructured data, classification problems, and natural language processing–related tasks. Additionally, the book looks at counterfactual explanations for AI models. Practical Explainable AI Using Python shines the light on deep learning models, rule-based expert systems, and computer vision tasks using various XAI frameworks. What You'll Learn Review the different ways of making an AI model interpretable and explainable Examine the biasness and good ethical practices of AI models Quantify, visualize, and estimate reliability of AI models Design frameworks to unbox the black-box models Assess the fairness of AI models Understand the building blocks of trust in AI models Increase the level of AI adoption Who This Book Is For AI engineers, data scientists, and software developers involved in driving AI projects/ AI products.
Explainable AI (XAI) for Sustainable Development
Author: Lakshmi D
Publisher: CRC Press
ISBN: 1040038832
Category : Technology & Engineering
Languages : en
Pages : 335
Book Description
This book presents innovative research works to automate, innovate, design, and deploy AI fo real-world applications. It discusses AI applications in major cutting-edge technologies and details about deployment solutions for different applications for sustainable development. The application of Blockchain techniques illustrates the ways of optimisation algorithms in this book. The challenges associated with AI deployment are also discussed in detail, and edge computing with machine learning solutions is explained. This book provides multi-domain applications of AI to the readers to help find innovative methods towards the business, sustainability, and customer outreach paradigms in the AI domain. • Focuses on virtual machine placement and migration techniques for cloud data centres • Presents the role of machine learning and meta-heuristic approaches for optimisation in cloud computing services • Includes application of placement techniques for quality of service, performance, and reliability improvement • Explores data centre resource management, load balancing and orchestration using machine learning techniques • Analyses dynamic and scalable resource scheduling with a focus on resource management The reference work is for postgraduate students, professionals, and academic researchers in computer science and information technology.
Publisher: CRC Press
ISBN: 1040038832
Category : Technology & Engineering
Languages : en
Pages : 335
Book Description
This book presents innovative research works to automate, innovate, design, and deploy AI fo real-world applications. It discusses AI applications in major cutting-edge technologies and details about deployment solutions for different applications for sustainable development. The application of Blockchain techniques illustrates the ways of optimisation algorithms in this book. The challenges associated with AI deployment are also discussed in detail, and edge computing with machine learning solutions is explained. This book provides multi-domain applications of AI to the readers to help find innovative methods towards the business, sustainability, and customer outreach paradigms in the AI domain. • Focuses on virtual machine placement and migration techniques for cloud data centres • Presents the role of machine learning and meta-heuristic approaches for optimisation in cloud computing services • Includes application of placement techniques for quality of service, performance, and reliability improvement • Explores data centre resource management, load balancing and orchestration using machine learning techniques • Analyses dynamic and scalable resource scheduling with a focus on resource management The reference work is for postgraduate students, professionals, and academic researchers in computer science and information technology.
Towards Digital Intelligence Society
Author: Ján Paralič
Publisher: Springer Nature
ISBN: 3030638723
Category : Technology & Engineering
Languages : en
Pages : 212
Book Description
This book aims to provide readers with up-to-date knowledge on how to make these technologies smarter. Humanity is now going through difficult times to fight the Covid-19 pandemic. Simultaneously, in these difficult times of physical separation, we can also realize how much digital society technology helps us cope with many difficulties that bring us this time. The authors focus on selected research challenges for intelligent digital society and state-of-the-art methods of how to face them. The book’s subtitle suggests that a core concept that the reader can study from various points of view in particular book chapters is the knowledge. The knowledge that can help us intelligently face different digital society challenges (Part I of this book); the knowledge extracted from available big data employing intelligent analysis techniques (Part II). For efficient processing and analysis of data, there is a strong need for smart data and information modeling techniques (Part III).
Publisher: Springer Nature
ISBN: 3030638723
Category : Technology & Engineering
Languages : en
Pages : 212
Book Description
This book aims to provide readers with up-to-date knowledge on how to make these technologies smarter. Humanity is now going through difficult times to fight the Covid-19 pandemic. Simultaneously, in these difficult times of physical separation, we can also realize how much digital society technology helps us cope with many difficulties that bring us this time. The authors focus on selected research challenges for intelligent digital society and state-of-the-art methods of how to face them. The book’s subtitle suggests that a core concept that the reader can study from various points of view in particular book chapters is the knowledge. The knowledge that can help us intelligently face different digital society challenges (Part I of this book); the knowledge extracted from available big data employing intelligent analysis techniques (Part II). For efficient processing and analysis of data, there is a strong need for smart data and information modeling techniques (Part III).