Alkhatib, Manar (18 results)

Condition: New.

Condition: New.

Condition: New.

Taschenbuch. Condition: Neu. Neuware - Artificial intelligence (AI) has emerged as one of the most transformative technologies of the 21st century, reshaping industries, economies, and the way societies address complex global challenges. Among its most promising applications is its ability to accelerate the transition to renewable energy and support more sustainable development. As the world confronts climate change, rising energy demands, and the need to reduce carbon emissions, intelligent technologies are playing an increasingly important role in optimizing energy production, improving system efficiency, and supporting smarter decision-making. AI offers new opportunities to enhance the reliability and resilience of renewable energy systems while enabling more effective management of energy resources. Understanding how these technologies can drive a cleaner and more sustainable energy future has become a critical priority for researchers, industry leaders, and policymakers alike. Sustaining Intelligent Societies Through Renewable Energy Sources for AI Development explores how AI can enhance and optimize renewable energy systems to build more resilient and sustainable societies. Rather than viewing AI as a burden on energy infrastructure, this book positions it as a transformative enabler capable of addressing the intermittent and variable nature of renewable energy, improving energy forecasting, advancing smart grid management, and driving innovation in energy storage. Covering topics such as thermal optimization, geothermal technologies, and hydrogen energy systems, this book is a fundamental academic resource for graduate and doctoral students, energy engineers, utility professionals, renewable energy specialists, smart grid researchers, infrastructure planners, technology professionals, sustainability professionals, environmental planners, policymakers, and more.…

Buch. Condition: Neu. Neuware - Artificial intelligence (AI) has emerged as one of the most transformative technologies of the 21st century, reshaping industries, economies, and the way societies address complex global challenges. Among its most promising applications is its ability to accelerate the transition to renewable energy and support more sustainable development. As the world confronts climate change, rising energy demands, and the need to reduce carbon emissions, intelligent technologies are playing an increasingly important role in optimizing energy production, improving system efficiency, and supporting smarter decision-making. AI offers new opportunities to enhance the reliability and resilience of renewable energy systems while enabling more effective management of energy resources. Understanding how these technologies can drive a cleaner and more sustainable energy future has become a critical priority for researchers, industry leaders, and policymakers alike. Sustaining Intelligent Societies Through Renewable Energy Sources for AI Development explores how AI can enhance and optimize renewable energy systems to build more resilient and sustainable societies. Rather than viewing AI as a burden on energy infrastructure, this book positions it as a transformative enabler capable of addressing the intermittent and variable nature of renewable energy, improving energy forecasting, advancing smart grid management, and driving innovation in energy storage. Covering topics such as thermal optimization, geothermal technologies, and hydrogen energy systems, this book is a fundamental academic resource for graduate and doctoral students, energy engineers, utility professionals, renewable energy specialists, smart grid researchers, infrastructure planners, technology professionals, sustainability professionals, environmental planners, policymakers, and more.…

PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condition: new. Paperback. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

HRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condition: new. Paperback. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Hardcover. Condition: new. Hardcover. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Condition: new. Hardcover. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condition: new. Paperback. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Computer vision has achieved remarkable success in controlled research environments, yet its deployment in real-world settings remains constrained by data variability, limited resources, security risks, and trust-related concerns. In practice, vision systems must operate reliably under noise, changing illumination, sensor imperfections, and shifting data distributions while adapting to dynamic environments. These challenges are amplified in safety-critical and socially sensitive contexts, where errors can carry significant consequences. As a result, building robust, secure, and trustworthy real-world image processing systems remains a central priority. Trustworthy Computer Vision for Real-World Image Processing: Robustness, Efficiency, and Deployment addresses the growing gap between laboratory-scale vision models and deployable, dependable systems. This book emphasizes robustness, computational efficiency, explainability, fairness, privacy preservation, and operational reliability as foundational requirements for modern computer vision applications. Rather than focusing solely on model accuracy, the book adopts a holistic perspective that considers trustworthiness across the full system lifecycle. Covering topics such as adversarial robustness and security, predictive maintenance in smart mining, and self-supervised representation learning, this book is an essential academic resource for graduate and doctoral students, computer vision engineers, software engineers, AI governance experts, policymakers, and more.…

Taschenbuch. Condition: Neu. Trustworthy Computer Vision for Real-World Image Processing | Robustness, Efficiency, and Deployment | Manar Alkhatib | Taschenbuch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798337392868 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …

Hardcover. Condition: new. Hardcover. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Computer vision has achieved remarkable success in controlled research environments, yet its deployment in real-world settings remains constrained by data variability, limited resources, security risks, and trust-related concerns. In practice, vision systems must operate reliably under noise, changing illumination, sensor imperfections, and shifting data distributions while adapting to dynamic environments. These challenges are amplified in safety-critical and socially sensitive contexts, where errors can carry significant consequences. As a result, building robust, secure, and trustworthy real-world image processing systems remains a central priority. Trustworthy Computer Vision for Real-World Image Processing: Robustness, Efficiency, and Deployment addresses the growing gap between laboratory-scale vision models and deployable, dependable systems. This book emphasizes robustness, computational efficiency, explainability, fairness, privacy preservation, and operational reliability as foundational requirements for modern computer vision applications. Rather than focusing solely on model accuracy, the book adopts a holistic perspective that considers trustworthiness across the full system lifecycle. Covering topics such as adversarial robustness and security, predictive maintenance in smart mining, and self-supervised representation learning, this book is an essential academic resource for graduate and doctoral students, computer vision engineers, software engineers, AI governance experts, policymakers, and more.…