chinnusamy karthikeyan (59 Ergebnisse)

hardcover. Zustand: Very Good. Explainable AI Applications for Human Behavior Analysis This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping.

hardcover. Zustand: Very Good. This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping.

Zustand: New.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Hardcover. Zustand: new. Hardcover. Pioneering AI and data technologies redefines next-generation security, Internet of Things (IoT), and smart ecosystems. By integrating intelligent algorithms with real-time data, these technologies enable more responsive, adaptive, and predictive systems across urban infrastructure, industrial environments, and connected devices. In security, AI strengthens threat detection and response, while in IoT, it enhances smarter automation and efficient resource management. Together with advanced data analytics, these innovations drive interconnected ecosystems that are more intelligent and secure, as well as more sustainable and resilient when facing global challenges. Pioneering AI and Data Technologies for Next-Gen Security, IoT, and Smart Ecosystems explores the integration of intelligent technologies into security, automation, and smart business sectors. It presents solutions for enhanced threat detection, data analysis, and predictive maintenance. This book covers topics such as digital technology, cloud computing, and deep learning, and is a useful resource for computer engineers, security professionals, business owners, academicians, researchers, and data scientists. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Zustand: As New. Unread book in perfect condition.

Paperback. Zustand: new. Paperback. Pioneering AI and data technologies redefines next-generation security, Internet of Things (IoT), and smart ecosystems. By integrating intelligent algorithms with real-time data, these technologies enable more responsive, adaptive, and predictive systems across urban infrastructure, industrial environments, and connected devices. In security, AI strengthens threat detection and response, while in IoT, it enhances smarter automation and efficient resource management. Together with advanced data analytics, these innovations drive interconnected ecosystems that are more intelligent and secure, as well as more sustainable and resilient when facing global challenges. Pioneering AI and Data Technologies for Next-Gen Security, IoT, and Smart Ecosystems explores the integration of intelligent technologies into security, automation, and smart business sectors. It presents solutions for enhanced threat detection, data analysis, and predictive maintenance. This book covers topics such as digital technology, cloud computing, and deep learning, and is a useful resource for computer engineers, security professionals, business owners, academicians, researchers, and data scientists. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Paperback. Zustand: new. Paperback. The integration of machine learning, predictive analytics, and optimization techniques revolutionizes the understanding and management of complex systems. From supply chains and energy grids to healthcare and financial markets, these systems are characterized by dynamic interactions, uncertainty, and large data amounts. Machine learning enables insights into data patterns, analytics predict future behaviors, and optimization methods guide decision-making. When combined, these tools offer solutions for enhancing system performance, resilience, and adaptability. As complexity grows, their collaboration becomes vital for creating intelligent, responsive, and sustainable systems. Machine Learning, Predictive Analytics, and Optimization in Complex Systems examines the integration of intelligent technologies into system design and management, and data analysis. It explores strategies for data-informed decisions, intelligent technology utilization, and security optimization. This book covers topics such as computer engineering, smart ecosystems, and system design, and is a useful resource for computer engineers, data analysts, academicians, researchers, and scientists. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Paperback. Zustand: new. Paperback. The landscape of healthcare is transformed by the integration of advanced data analytics, especially in the realm of multi-source data analysis. By combining diverse datasets, such as electronic health records (EHRs), genetic information, wearable device data, and patient-reported outcomes, healthcare providers can gain a comprehensive understanding of a patient's health status. This approach creates more personalized treatment plans, enhances diagnostic accuracy, and supports early detection of potential health issues. Communication between various data sources allows for the identification of hidden trends and patterns, improving predictive capabilities and optimizing patient outcomes. As healthcare systems adopt this data-driven process, it is crucial to address challenges related to data privacy, integration, and the interpretation of complex datasets, ensuring the potential benefits of multi-source data analysis are realized in ethical and effective ways. Optimizing Patient Outcomes Through Multi-Source Data Analysis in Healthcare explores the transformative potential of big data and AI in healthcare, focusing on informed decision-making. It delves into the integration of vast, diverse datasets, analyzed through AI algorithms to enhance patient outcomes and operational efficiency. This book covers topics such as automation, machine learning, and neural networks, and is a useful resource for healthcare professionals, computer engineers, business owners, academicians, researchers, and data scientists. "This book explores the transformative potential of big data and AI in healthcare, focusing on informed decision-making. It delves into the integration of vast, diverse datasets such as EHRs, medical imaging, and genomic data, analyzed through AI algorithms to enhance patient outcomes and operational efficiency"-- Provided by publisher. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 388 | Sprache: Englisch | Produktart: Bücher | The study of learning versus teaching development has a significant impact on facilitating learners' development to use ICT-based digital technology. As innovation has developed, it has also changed how instructors connect with their understudies and study halls. To better understand these technological developments, further study is required. The Handbook of Research on Learning in Language Classrooms Through ICT-Based Digital Technology considers technology from the fields of ICT-based digital technology, facilitating learning, teaching development, language, and linguistics. This book also assesses the effectiveness of technology uses in ICT-based digital technology and language classrooms as well as considers the successful methods of teaching and language topics in the teaching-learning phase through technology. Covering key topics such as artificial intelligence, gamification, media, and technology tools, this premier reference source is ideal for computer scientists, administrators, principals, researchers, academicians, practitioners, scholars, instructors, and students.

Hardcover. Zustand: new. Hardcover. Pioneering AI and data technologies redefines next-generation security, Internet of Things (IoT), and smart ecosystems. By integrating intelligent algorithms with real-time data, these technologies enable more responsive, adaptive, and predictive systems across urban infrastructure, industrial environments, and connected devices. In security, AI strengthens threat detection and response, while in IoT, it enhances smarter automation and efficient resource management. Together with advanced data analytics, these innovations drive interconnected ecosystems that are more intelligent and secure, as well as more sustainable and resilient when facing global challenges. Pioneering AI and Data Technologies for Next-Gen Security, IoT, and Smart Ecosystems explores the integration of intelligent technologies into security, automation, and smart business sectors. It presents solutions for enhanced threat detection, data analysis, and predictive maintenance. This book covers topics such as digital technology, cloud computing, and deep learning, and is a useful resource for computer engineers, security professionals, business owners, academicians, researchers, and data scientists. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Zustand: New. In.

Hardcover. Zustand: new. Hardcover. The integration of machine learning, predictive analytics, and optimization techniques revolutionizes the understanding and management of complex systems. From supply chains and energy grids to healthcare and financial markets, these systems are characterized by dynamic interactions, uncertainty, and large data amounts. Machine learning enables insights into data patterns, analytics predict future behaviors, and optimization methods guide decision-making. When combined, these tools offer solutions for enhancing system performance, resilience, and adaptability. As complexity grows, their collaboration becomes vital for creating intelligent, responsive, and sustainable systems. Machine Learning, Predictive Analytics, and Optimization in Complex Systems examines the integration of intelligent technologies into system design and management, and data analysis. It explores strategies for data-informed decisions, intelligent technology utilization, and security optimization. This book covers topics such as computer engineering, smart ecosystems, and system design, and is a useful resource for computer engineers, data analysts, academicians, researchers, and scientists. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Hardcover. Zustand: new. Hardcover. The landscape of healthcare is transformed by the integration of advanced data analytics, especially in the realm of multi-source data analysis. By combining diverse datasets, such as electronic health records (EHRs), genetic information, wearable device data, and patient-reported outcomes, healthcare providers can gain a comprehensive understanding of a patient's health status. This approach creates more personalized treatment plans, enhances diagnostic accuracy, and supports early detection of potential health issues. Communication between various data sources allows for the identification of hidden trends and patterns, improving predictive capabilities and optimizing patient outcomes. As healthcare systems adopt this data-driven process, it is crucial to address challenges related to data privacy, integration, and the interpretation of complex datasets, ensuring the potential benefits of multi-source data analysis are realized in ethical and effective ways. Optimizing Patient Outcomes Through Multi-Source Data Analysis in Healthcare explores the transformative potential of big data and AI in healthcare, focusing on informed decision-making. It delves into the integration of vast, diverse datasets, analyzed through AI algorithms to enhance patient outcomes and operational efficiency. This book covers topics such as automation, machine learning, and neural networks, and is a useful resource for healthcare professionals, computer engineers, business owners, academicians, researchers, and data scientists. "This book explores the transformative potential of big data and AI in healthcare, focusing on informed decision-making. It delves into the integration of vast, diverse datasets such as EHRs, medical imaging, and genomic data, analyzed through AI algorithms to enhance patient outcomes and operational efficiency"-- Provided by publisher. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Zustand: Neu. Neuware.

Paperback. Zustand: New. The rise of Artificial Intelligence (AI) amidst the backdrop of a world that is changing at lightning speed presents a whole new set of challenges. One of our biggest hurdles is more transparency in AI solutions. It's a complex issue, but one that we need to address if we want to ensure that the benefits of AI are accessible to everyone. Across diverse sectors such as healthcare, surveillance, and human-computer interaction, the inability to understand and evaluate AI's decision-making processes hinders progress and raises concerns about accountability. Cross-Industry AI Applications is a groundbreaking solution to illuminate the mysteries of AI-driven human behavior analysis. This pioneering book addresses the necessity of transparency and explainability in AI systems, particularly in analyzing human behavior. Compiling insights from leading experts and academics offers a comprehensive exploration of state-of-the-art methodologies, benchmarks, and systems for understanding and predicting human behavior using AI. Each chapter delves into novel approaches and real-world applications, from facial expressions to gesture recognition, providing invaluable knowledge for scholars and professionals alike. With its focus on explainable AI and its implications for decision-making, Cross-Industry AI Applications serves as a roadmap for navigating the complexities of human behavior analysis in the age of AI. By offering clarity and insight into AI algorithms and their impact on diverse industries, this book empowers readers to harness the full potential of AI while ensuring accountability and ethical practice. Join the forefront of AI research and innovation - order your copy today and embark on a transformative journey into the future of human-AI interaction.

Zustand: New.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Zustand: As New. Unread book in perfect condition.

Hardback. Zustand: New. The rise of Artificial Intelligence (AI) amidst the backdrop of a world that is changing at lightning speed presents a whole new set of challenges. One of our biggest hurdles is more transparency in AI solutions. It's a complex issue, but one that we need to address if we want to ensure that the benefits of AI are accessible to everyone. Across diverse sectors such as healthcare, surveillance, and human-computer interaction, the inability to understand and evaluate AI's decision-making processes hinders progress and raises concerns about accountability. Cross-Industry AI Applications is a groundbreaking solution to illuminate the mysteries of AI-driven human behavior analysis. This pioneering book addresses the necessity of transparency and explainability in AI systems, particularly in analyzing human behavior. Compiling insights from leading experts and academics offers a comprehensive exploration of state-of-the-art methodologies, benchmarks, and systems for understanding and predicting human behavior using AI. Each chapter delves into novel approaches and real-world applications, from facial expressions to gesture recognition, providing invaluable knowledge for scholars and professionals alike. With its focus on explainable AI and its implications for decision-making, Cross-Industry AI Applications serves as a roadmap for navigating the complexities of human behavior analysis in the age of AI. By offering clarity and insight into AI algorithms and their impact on diverse industries, this book empowers readers to harness the full potential of AI while ensuring accountability and ethical practice. Join the forefront of AI research and innovation - order your copy today and embark on a transformative journey into the future of human-AI interaction.

Zustand: New.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Zustand: As New. Unread book in perfect condition.

Hardback. Zustand: New. The rise of Artificial Intelligence (AI) amidst the backdrop of a world that is changing at lightning speed presents a whole new set of challenges. One of our biggest hurdles is more transparency in AI solutions. It's a complex issue, but one that we need to address if we want to ensure that the benefits of AI are accessible to everyone. Across diverse sectors such as healthcare, surveillance, and human-computer interaction, the inability to understand and evaluate AI's decision-making processes hinders progress and raises concerns about accountability. Cross-Industry AI Applications is a groundbreaking solution to illuminate the mysteries of AI-driven human behavior analysis. This pioneering book addresses the necessity of transparency and explainability in AI systems, particularly in analyzing human behavior. Compiling insights from leading experts and academics offers a comprehensive exploration of state-of-the-art methodologies, benchmarks, and systems for understanding and predicting human behavior using AI. Each chapter delves into novel approaches and real-world applications, from facial expressions to gesture recognition, providing invaluable knowledge for scholars and professionals alike. With its focus on explainable AI and its implications for decision-making, Cross-Industry AI Applications serves as a roadmap for navigating the complexities of human behavior analysis in the age of AI. By offering clarity and insight into AI algorithms and their impact on diverse industries, this book empowers readers to harness the full potential of AI while ensuring accountability and ethical practice. Join the forefront of AI research and innovation - order your copy today and embark on a transformative journey into the future of human-AI interaction.

Paperback. Zustand: New. The rise of Artificial Intelligence (AI) amidst the backdrop of a world that is changing at lightning speed presents a whole new set of challenges. One of our biggest hurdles is more transparency in AI solutions. It's a complex issue, but one that we need to address if we want to ensure that the benefits of AI are accessible to everyone. Across diverse sectors such as healthcare, surveillance, and human-computer interaction, the inability to understand and evaluate AI's decision-making processes hinders progress and raises concerns about accountability. Cross-Industry AI Applications is a groundbreaking solution to illuminate the mysteries of AI-driven human behavior analysis. This pioneering book addresses the necessity of transparency and explainability in AI systems, particularly in analyzing human behavior. Compiling insights from leading experts and academics offers a comprehensive exploration of state-of-the-art methodologies, benchmarks, and systems for understanding and predicting human behavior using AI. Each chapter delves into novel approaches and real-world applications, from facial expressions to gesture recognition, providing invaluable knowledge for scholars and professionals alike. With its focus on explainable AI and its implications for decision-making, Cross-Industry AI Applications serves as a roadmap for navigating the complexities of human behavior analysis in the age of AI. By offering clarity and insight into AI algorithms and their impact on diverse industries, this book empowers readers to harness the full potential of AI while ensuring accountability and ethical practice. Join the forefront of AI research and innovation - order your copy today and embark on a transformative journey into the future of human-AI interaction.

Paperback. Zustand: new. Paperback. Pioneering AI and data technologies redefines next-generation security, Internet of Things (IoT), and smart ecosystems. By integrating intelligent algorithms with real-time data, these technologies enable more responsive, adaptive, and predictive systems across urban infrastructure, industrial environments, and connected devices. In security, AI strengthens threat detection and response, while in IoT, it enhances smarter automation and efficient resource management. Together with advanced data analytics, these innovations drive interconnected ecosystems that are more intelligent and secure, as well as more sustainable and resilient when facing global challenges. Pioneering AI and Data Technologies for Next-Gen Security, IoT, and Smart Ecosystems explores the integration of intelligent technologies into security, automation, and smart business sectors. It presents solutions for enhanced threat detection, data analysis, and predictive maintenance. This book covers topics such as digital technology, cloud computing, and deep learning, and is a useful resource for computer engineers, security professionals, business owners, academicians, researchers, and data scientists. 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. Zustand: new. Paperback. The integration of machine learning, predictive analytics, and optimization techniques revolutionizes the understanding and management of complex systems. From supply chains and energy grids to healthcare and financial markets, these systems are characterized by dynamic interactions, uncertainty, and large data amounts. Machine learning enables insights into data patterns, analytics predict future behaviors, and optimization methods guide decision-making. When combined, these tools offer solutions for enhancing system performance, resilience, and adaptability. As complexity grows, their collaboration becomes vital for creating intelligent, responsive, and sustainable systems. Machine Learning, Predictive Analytics, and Optimization in Complex Systems examines the integration of intelligent technologies into system design and management, and data analysis. It explores strategies for data-informed decisions, intelligent technology utilization, and security optimization. This book covers topics such as computer engineering, smart ecosystems, and system design, and is a useful resource for computer engineers, data analysts, academicians, researchers, and scientists. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.