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Synopsis
In the field of computer vision research, the study of human behavior is a formidable challenge. The diverse applications of this field, from video surveillance for crowd analysis to healthcare diagnostics, have drawn increasing attention. However, a significant problem persists - the sacrifice of transparency for the sake of predictive accuracy in Artificial Intelligence (AI) solutions. These AI systems often operate as enigmatic black boxes, seemingly conjuring decisions from vast datasets with little to no explanation. The need for clarity and accountability in AI decision-making is paramount as our reliance on these systems continues to grow. Explainable AI Applications for Human Behavior Analysis embarks on a mission to harness AI's innate capability to elucidate upon its own decision-making processes. By focusing on facial expressions, gestures, and body movements, we delve into uncharted territories of research, offering novel methodologies, databases, benchmarks, and algorithms for the analysis of human behavior in natural settings. Geared toward academic scholars, this book compiles the expertise of leading researchers in the field, making it accessible to readers of all educational backgrounds.
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About the Authors
S. Suman Rajest is currently working as Dean of Research and Development (R&D) & International Student Affairs (ISA) at Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India. He is an Editor in Chief of the International Journal of Human Computing Studies and The International Journal of Social Sciences World, He is the Chief Executive Editor of the International Journal of Advanced Engineering Research and Science, International Journal of Advanced Engineering, Management and Science, The International Journal of Health and Medicines, The International Journal of Management Economy and Accounting Fields and The International Journal of Technology Information and Computer and also he is an Editorial Board Member in International Journal of Management in Education, Scopus, Inderscience, EAI Endorsed Transactions on e-Learning, and Bulletin of the Karaganda university Pedagogy series. He is also a Book Series Editor in IGI Global Publisher, Springer, etc. All of his writing, including his research, involves elements of creative nonfiction in the Human Computing learning system. He is also interested in creative writing and digital media, Learning, AI, student health learning, etc. He has published 200 papers in peer-reviewed international journals. He has authored and co-authored several scientific book publications in journals and conferences and is a frequent reviewer of international journals and international conferences and also, he is also a reviewer in Inderscience, EAI Journals, IGI Global, Science Publications, etc.
Karthikeyan Chinnusamy is Sr Principal with more than 25 years of experience in IT, Product Dev, R&D and Education fields. Fellow IETE, Fellow IE, Sr Member IEEE, Sr Member ACM, Project management Institute (PMI), Reviewer, Editorial Board Member of R&D Journals. Board Member & Program Director SF DAMA. SME in Data Governance, GDPR, HIPAA Compliance, Data Management, Data Architecture, Master Data, Data Quality, AI/ML, Analytics and reporting in Payment processing, Customer, Finance, CRM and License domains. Mentor in SFDC Mig, Data.com, ERP, Architecture, R&D, Embedded systems, VLSI, Adv Information processing. I am also reviewer for IEEE Silicon Valley Sr Member Elevation and Speaker, Volunteer for SFBay ACM. Reviewer of Journals in Springer Nature.
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- PublisherIGI Global
- Publication date2024
- ISBN 13 9798369313558
- BindingHardcover
- LanguageEnglish
- Number of pages320
- EditorParamasivan P, Rajest S Suman, Chinnusamy Karthikeyan
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Hardcover. Condition: new. Hardcover. In the field of computer vision research, the study of human behavior is a formidable challenge. The diverse applications of this field, from video surveillance for crowd analysis to healthcare diagnostics, have drawn increasing attention. However, a significant problem persists the sacrifice of transparency for the sake of predictive accuracy in Artificial Intelligence (AI) solutions. These AI systems often operate as enigmatic black boxes, seemingly conjuring decisions from vast datasets with little to no explanation. The need for clarity and accountability in AI decision-making is paramount as our reliance on these systems continues to grow. Explainable AI Applications for Human Behavior Analysis embarks on a mission to harness AI's innate capability to elucidate upon its own decision-making processes. By focusing on facial expressions, gestures, and body movements, we delve into uncharted territories of research, offering novel methodologies, databases, benchmarks, and algorithms for the analysis of human behavior in natural settings. Geared toward academic scholars, this book compiles the expertise of leading researchers in the field, making it accessible to readers of all educational backgrounds. It bridges the gap between technical depth and ease of comprehension, featuring quick-reference infographics and an array of topics. The aim is not only to inform but also to encourage knowledge sharing among peers. Join us in the exploration of this technology's transformative potential in decoding human behavior, a journey that promotes clarity, innovation, and accountability for our AI-driven future. Explores AIs innate capability to elucidate upon its own decision-making processes. By focusing on facial expressions, gestures, and body movements, the book delves into uncharted territories of research, offering novel methodologies, databases, benchmarks, and algorithms for the analysis of human behaviour in natural settings. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798369313558
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