Author: Xiaoping Zheng
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Explainable Artificial Intelligence in Movement Sciences
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
Author: Wojciech Samek
Publisher: Springer Nature
ISBN: 3030289540
Category : Computers
Languages : en
Pages : 435
Book Description
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.
Publisher: Springer Nature
ISBN: 3030289540
Category : Computers
Languages : en
Pages : 435
Book Description
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.
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.
Explainable Artificial Intelligence
Author: Luca Longo
Publisher: Springer Nature
ISBN: 3031440676
Category : Computers
Languages : en
Pages : 676
Book Description
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.
Publisher: Springer Nature
ISBN: 3031440676
Category : Computers
Languages : en
Pages : 676
Book Description
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.
Computational Intelligence for Movement Sciences: Neural Networks and Other Emerging Techniques
Author: Begg, Rezaul
Publisher: IGI Global
ISBN: 1591408385
Category : Computers
Languages : en
Pages : 396
Book Description
"This book provides information regarding state-of-the-art research outcomes and cutting-edge technology on various aspects of the human movement"--Provided by publisher.
Publisher: IGI Global
ISBN: 1591408385
Category : Computers
Languages : en
Pages : 396
Book Description
"This book provides information regarding state-of-the-art research outcomes and cutting-edge technology on various aspects of the human movement"--Provided by publisher.
Insights in movement science and sport psychology 2021
Author: Guy Cheron
Publisher: Frontiers Media SA
ISBN: 2832535143
Category : Science
Languages : en
Pages : 152
Book Description
Publisher: Frontiers Media SA
ISBN: 2832535143
Category : Science
Languages : en
Pages : 152
Book Description
Deep Learning Techniques for Biomedical and Health Informatics
Author: Basant Agarwal
Publisher: Academic Press
ISBN: 0128190620
Category : Science
Languages : en
Pages : 367
Book Description
Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they are applied to Biomedical Engineering, Electronic Health Records, and medical image processing. Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including Deep Learning for drug discovery, clinical decision support systems, disease diagnosis, prediction and monitoring Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis
Publisher: Academic Press
ISBN: 0128190620
Category : Science
Languages : en
Pages : 367
Book Description
Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they are applied to Biomedical Engineering, Electronic Health Records, and medical image processing. Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including Deep Learning for drug discovery, clinical decision support systems, disease diagnosis, prediction and monitoring Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis
Computational Intelligence for Movement Sciences
Machine Learning Approaches to Human Movement Analysis
Author: Matteo Zago
Publisher: Frontiers Media SA
ISBN: 2889665615
Category : Science
Languages : en
Pages : 328
Book Description
Publisher: Frontiers Media SA
ISBN: 2889665615
Category : Science
Languages : en
Pages : 328
Book Description
Human Movement Understanding
Author: P. Morasso
Publisher: Elsevier
ISBN: 0080866875
Category : Psychology
Languages : en
Pages : 393
Book Description
The volume applies to the study of the motor system the computational approach developed by David Marr for the visual system. Accordingly, understanding movement is viewed as an information processing problem, centred on the representation of appropriate computational structures. In particular, the book deals with the representation of objects, concurrent parallel processes, trajectory formation patterns and patterns of interaction with the environment.A number of modeling techniques are discussed, ranging from computational geometry to artificial intelligence, integrating very different aspects of movement, especially those which are not directly motoric.
Publisher: Elsevier
ISBN: 0080866875
Category : Psychology
Languages : en
Pages : 393
Book Description
The volume applies to the study of the motor system the computational approach developed by David Marr for the visual system. Accordingly, understanding movement is viewed as an information processing problem, centred on the representation of appropriate computational structures. In particular, the book deals with the representation of objects, concurrent parallel processes, trajectory formation patterns and patterns of interaction with the environment.A number of modeling techniques are discussed, ranging from computational geometry to artificial intelligence, integrating very different aspects of movement, especially those which are not directly motoric.