Mathematical Models Using Artificial Intelligence for Surveillance Systems (eBook)
360 Seiten
Wiley-Scrivener (Verlag)
978-1-394-20072-6 (ISBN)
This book gives comprehensive insights into the application of AI, machine learning, and deep learning in developing efficient and optimal surveillance systems for both indoor and outdoor environments, addressing the evolving security challenges in public and private spaces.
Mathematical Models Using Artificial Intelligence for Surveillance Systems aims to collect and publish basic principles, algorithms, protocols, developing trends, and security challenges and their solutions for various indoor and outdoor surveillance applications using artificial intelligence (AI). The book addresses how AI technologies such as machine learning (ML), deep learning (DL), sensors, and other wireless devices could play a vital role in assisting various security agencies. Security and safety are the major concerns for public and private places in every country. Some places need indoor surveillance, some need outdoor surveillance, and, in some places, both are needed. The goal of this book is to provide an efficient and optimal surveillance system using AI, ML, and DL-based image processing.
The blend of machine vision technology and AI provides a more efficient surveillance system compared to traditional systems. Leading scholars and industry practitioners are expected to make significant contributions to the chapters. Their deep conversations and knowledge, which are based on references and research, will result in a wonderful book and a valuable source of information.
Padmesh Tripathi, PhD, is an associate professor of mathematics at the Indian Institute of Management and Technology College of Engineering, Greater Noida, India. He has more than 20 years of teaching experience. Additionally, he has published several research papers and book chapters in reputed journals, as well as presented papers and participated in many national and international conferences and workshops.
Mritunjay Rai is an assistant professor in the Department of Electronics and Communication at Shri Ramswaroop Memorial University, India. He has more than ten years of working experience in research and academics. Additionally, he has published many research articles in reputed journals and contributed many chapters in books, as well as reviewed many research papers in journals and national and international conferences.
Nitendra Kumar, PhD, is an assistant professor at the Indian Institute of Management and Technology College of Engineering, Greater Noida. He has more than 10 years of experience in his research areas and has published many research papers in reputed journals and six books on engineering mathematics. He contributes to the research community by volunteering to edit and has edited two books.
Santosh Kumar, PhD, is an assistant professor in the Department of Mathematics, School of Basic Sciences and Research, Sharda University, India. He has published ten research papers in the SCOPUS indexed journals, as well as two Indian patents. Dr. Kumar has published ten book chapters with reputed publishers. He has attended many national and international conferences and faculty development programs and workshops and has given many talks, and chairing sessions at both the national and international levels.
This book gives comprehensive insights into the application of AI, machine learning, and deep learning in developing efficient and optimal surveillance systems for both indoor and outdoor environments, addressing the evolving security challenges in public and private spaces. Mathematical Models Using Artificial Intelligence for Surveillance Systems aims to collect and publish basic principles, algorithms, protocols, developing trends, and security challenges and their solutions for various indoor and outdoor surveillance applications using artificial intelligence (AI). The book addresses how AI technologies such as machine learning (ML), deep learning (DL), sensors, and other wireless devices could play a vital role in assisting various security agencies. Security and safety are the major concerns for public and private places in every country. Some places need indoor surveillance, some need outdoor surveillance, and, in some places, both are needed. The goal of this book is to provide an efficient and optimal surveillance system using AI, ML, and DL-based image processing. The blend of machine vision technology and AI provides a more efficient surveillance system compared to traditional systems. Leading scholars and industry practitioners are expected to make significant contributions to the chapters. Their deep conversations and knowledge, which are based on references and research, will result in a wonderful book and a valuable source of information.
Erscheint lt. Verlag | 31.7.2024 |
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Sprache | englisch |
Themenwelt | Mathematik / Informatik ► Informatik ► Theorie / Studium |
Schlagworte | Advanced Surveillance System</p> • Artificial Intelligence • Background Frame • Background Subtraction (BGS) • Convolution Neural Network • Deep learning • Gaussian mixture model (GMM) • <p>Foreground Frame • machine learning • Support Vector Machine • Surveillance system |
ISBN-10 | 1-394-20072-2 / 1394200722 |
ISBN-13 | 978-1-394-20072-6 / 9781394200726 |
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