As online learning becomes increasingly central to education, maintaining student engagement and fostering growth remain fundamental challenges. Advances in AI and deep learning now allow for the detection and analysis of learner engagement in real time, using camera-based emotion recognition and adaptive models. By providing a non-invasive, responsive framework, these technologies can enhance attention, motivation, and cognitive skill development, creating more personalized and effective digital learning experiences. Deep Learning for Engagement and Cognitive Growth in E-Learning critically explores the integration of deep learning and AI to detect, analyze, and enhance student engagement in digital learning platforms. Leveraging camera-based emotion recognition systems and real-time engagement models, the book presents a novel framework that supports cognitive skill development in e-learning without relying on physiological signals. Covering topics such as camera-based deep learning, deepfake detection, and personalized learning pathways, this book is an excellent academic resource for graduate and doctoral students, academicians and policymakers in higher education, administrators, researchers, and more.
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Noor Zaman Jhanjhi is a distinguished Senior Professor of Computer Science at Taylor's University, Malaysia, where he specializes in Artificial Intelligence and Cybersecurity. As the Director of the Research Centre, Centre for Intelligent Innovation CII, and Program Director for Postgraduate Research Degree Programmes, he plays a pivotal role in shaping academic excellence and driving cutting-edge research initiatives. Globally acclaimed for his scholarly contributions, Prof. Jhanjhi has been consistently ranked among the world's top 2% research scientists (2022, 2023, 2024, and 2025) and stands as one of the Malaysia's top computer science researchers. He has been named amongst the top 0.05% of all scholars worldwide according to the 2025 ScholarGPS rankings. His exceptional work has earned him prestigious accolades, including the Outstanding Faculty Member Award (MDEC Malaysia, 2022) and the Vice Chancellor's Best Research Citations Award (Taylor's University, 2023). A prolific author and editor, Prof. Jhanjhi has published over 90 research books with leading publishers such as Springer, Elsevier, IGI Global, Bentham, IET, and Wiley etc., amassing 1,000+ impact factor points. His mentorship spans 45 postgraduate completions, and he has examined 80+ PhD and Master's theses worldwide. As an Editor-in-Chief, Associate Editor, and Editorial Board member for top-tier journals (PeerJ Computer Science, IEEE Access, CMC Computers), he advances scholarly discourse. His leadership extends to securing 40+ international research grants, underscoring his influence in innovation. A dynamic keynote speaker, Prof. Jhanjhi, has delivered 100+ invited talks and chaired major conferences. His decade-long engagement with ABET, NCAAA, and NCEAC accreditation bodies highlights his dedication to global academic standards. Combining research brilliance, academic leadership, and a passion for mentorship, Prof. Jhanjhi continues to inspire the next generation of computer scientists while shaping the future of AI and cybersecurity.
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - As online learning becomes increasingly central to education, maintaining student engagement and fostering growth remain fundamental challenges. Advances in AI and deep learning now allow for the detection and analysis of learner engagement in real time, using camera-based emotion recognition and adaptive models. By providing a non-invasive, responsive framework, these technologies can enhance attention, motivation, and cognitive skill development, creating more personalized and effective digital learning experiences. Deep Learning for Engagement and Cognitive Growth in E-Learning critically explores the integration of deep learning and AI to detect, analyze, and enhance student engagement in digital learning platforms. Leveraging camera-based emotion recognition systems and real-time engagement models, the book presents a novel framework that supports cognitive skill development in e-learning without relying on physiological signals. Covering topics such as camera-based deep learning, deepfake detection, and personalized learning pathways, this book is an excellent academic resource for graduate and doctoral students, academicians and policymakers in higher education, administrators, researchers, and more. Seller Inventory # 9798337365817
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