This book delves into the history of biometrics, the various systems that have been developed to date, the problems that have arisen from these systems, the necessity of AI-based biometrics systems, the various AI techniques.
This book delves into the history of biometrics, the various systems that have been developed to date, the problems that have arisen from these systems, the necessity of AI-based biometrics systems, the various AI techniques.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Dr. Balasubramaniam S (IEEE Senior Member) is working as an Assistant Professor in School of Computer Science and Engineering, Kerala University of Digital Sciences, Innovation and Technology (Formerly IIITM-K), Digital University Kerala, Thiruvananthapuram, Kerala, India. He has totally around 15+ years of experience in teaching, research and industry. He has completed his Post Doctoral Research in Department of Applied Data Science, Noroff University College, Kristiansand, Norway. He holds a Ph.D degree in Computer Science and Engineering from Anna University, Chennai, India in 2015. He has published nearly 25+ research papers in reputed SCI/WoS/Scopus indexed Journals. He has also granted with 1 Australian patent and 2 Indian Patents and published 2 Indian patents. He has presented papers at conferences, contributed chapters to the edited books and editor in few books published by international publishers. His research and publication interests include machine learning and deep learning-based disease diagnosis, cloud computing security, Generative AI and Electric Vehicles. Prof. Seifedine Kadry has a bachelor's degree in 1999 from Lebanese University, MS degree in 2002 from Reims University (France) and EPFL (Lausanne), PhD in 2007 from Blaise Pascal University (France), HDR degree in 2017 from Rouen University (France). At present his research focuses on Data Science, education using technology, system prognostics, stochastic systems, and applied mathematics. He is an ABET program evaluator for computing, and ABET program evaluator for Engineering Tech. he is a full professor of data science at Noroff University College, Norway and Department of Computer Science, Lebanese American University, Beirut, Lebanon. Prof. Manoj Kumar T K, currently serving as Dean (Research) and Professor at Kerala University of Digital Sciences, Innovation and Technology, Thiruvananthapuram, Kerala, India. He is having 5 years of post-doctoral research experience in prestigious institutions like IIT-Madras and Pohang University of Science & Technology, Korea. With an impressive 17-year track record in post-graduate teaching, Dr Manoj has imparted knowledge across a diverse range of subjects including Data Analytics, Deep Learning, Computational Sciences, Predictive Analytics, Big data technologies and Cloud computing, Discrete mathematics, Ordinary differential Equations, Automata, Data Structure and Algorithm, Artificial Intelligence, and Quantum Chemistry. Their scholarly contributions extend to 80 publications in international journals of high impact, marking a significant impact in their respective fields. Previously, he has holding key administrative roles such as Chair of the School of Digital Sciences; Registrar, Digital University Kerala; Registrar, Indian Institute of Information Technology and Management - Kerala and Director of the International Centre for Free and Open-Source Systems, Kerala, India. Prof. K. Satheesh Kumar presently holds the role of Visiting Professor at the Kerala University of Digital Sciences, Innovation, and Technology, Thiruvananthapuram Kerala, India. Previously, he served as Professor and Head of the Department of Futures Studies at the University of Kerala, Kerala, India. Dr. Kumar's academic journey began with a degree in mathematics, followed by doctoral research in suspension rheology and chaotic dynamics at the CSIR Lab in Thiruvananthapuram. He subsequently pursued post-doctoral research positions at Monash University, Australia, and POSTECH, South Korea. Dr. Kumar's research interests span suspension and polymer rheology, chaotic dynamics, nonlinear time series analysis, geophysics, complex network analysis, and wind energy modeling and forecasting.
Inhaltsangabe
Preface. 1 Potential Benefits of BIAs based ML/DL Models. 2 BIAs based Deep Learning (DL) Models. 3 Evaluation of Bio Inspired Algorithm based Machine Learning and Deep Learning Models. 4 Disease Diagnosis: Traditional vs. Bio Inspired Algorithm Approaches. 5 Algorithmic Heartbeat with Bio Inspired Algorithms in Cardiac Health Monitoring. 6 Bio Inspired Algorithms based Machine Learning and Deep Learning Models for Covid 19 Diagnosis. 7 Bio Inspired Intelligence in Early Cancer Detection: A Machine Learning Approach. 8 Bio Inspired Algorithms in Machine Learning and Deep Learning for Diabetes Diagnosis. 9 A Multi objective Optimized Bio inspired Deep Learning framework for Autism Spectrum Disorder Diagnosis in Toddlers. 10 Bio Inspired Algorithms using Machine Learning and Deep Learning for Social Phobia Treatment. 11 Bio Inspired Algorithms based Machine Learning models for Neural Disorders Prediction: A Focus on Depression Detection. 12 Research Directions and Challenges in Bio Inspired Algorithms for Machine Learning and Deep Learning Models in Healthcare. Index.
Preface. 1 Potential Benefits of BIAs based ML/DL Models. 2 BIAs based Deep Learning (DL) Models. 3 Evaluation of Bio Inspired Algorithm based Machine Learning and Deep Learning Models. 4 Disease Diagnosis: Traditional vs. Bio Inspired Algorithm Approaches. 5 Algorithmic Heartbeat with Bio Inspired Algorithms in Cardiac Health Monitoring. 6 Bio Inspired Algorithms based Machine Learning and Deep Learning Models for Covid 19 Diagnosis. 7 Bio Inspired Intelligence in Early Cancer Detection: A Machine Learning Approach. 8 Bio Inspired Algorithms in Machine Learning and Deep Learning for Diabetes Diagnosis. 9 A Multi objective Optimized Bio inspired Deep Learning framework for Autism Spectrum Disorder Diagnosis in Toddlers. 10 Bio Inspired Algorithms using Machine Learning and Deep Learning for Social Phobia Treatment. 11 Bio Inspired Algorithms based Machine Learning models for Neural Disorders Prediction: A Focus on Depression Detection. 12 Research Directions and Challenges in Bio Inspired Algorithms for Machine Learning and Deep Learning Models in Healthcare. Index.
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