nach der Bestellung gedruckt Neuware - Printed after ordering - Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.

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Bibliographic Details

Title: Machine Learning and Deep Learning in Real-Time Applications
Publisher: Engineering Science Reference
Publication Date: 2020
Language: English
ISBN 10: 1799830950
ISBN 13: 9781799830955
Binding: Buch
Condition: Neu
Dimensions: 286 millimeters width by 221 millimeters height by 25 millimeters depth
Weight: 1194 grams

About this title

Synopsis

Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.

About the Authors

Mehul Mahrishi is currently working as an Associate Professor in the faculty of computer Science & Engineering at the Swami Keshvanand Institute of Technology, Management and Gramothan, Jaipur – India. He is a Professional Member of IEEE Delhi Section, Life Member of Institution of Engineers, India (L-IEI) and Life member of International Association of Engineers (IAENG). He was a member of an Indian contingent of BRICS International Forum that travelled to Moscow, Russia to attend Russian Energy Week-2018 and BRICS Youth Energy Summit. He has published more than 20 research papers in national and international Journals/conferences including 19th ISDA, 4th SoCTA, 3rd International Conference on Machine Learning and Computing (ICMLC 2011), 3rd IACC 2013 and chapters in books. He has also participated in a range of forums by Infosys, TCS, and WIPRO-Mission 10 X, IBM etc. His research activities are currently twofold: while the first research activity is set to explore the developmental enhancements in applications in computer vision; the second major research theme focused on the emerging capabilities of parallel and cloud computing. Mr. Mahrishi is rewarded at number of occasions in various domains including Recognition as an active reviewer by Journal of Parallel and Distributed Computing (JPDC, Elsevier, and SCI & Scopus Indexed), IEEE continuing education certification for “Cloud Computing Enable Technologies and Recognition for outstanding performance in Campus Connect Program by Infosys, India.

Kamal Hiran has over 18 years of experience in academia, research, and administration in Asia, Africa, Europe, and North America. Currently he is working as Associate Professor in the School of Computer Science and IT, Symbiosis University of Applied Sciences, Indore, India and Adjunct Research Fellow at the Aalborg University, Copenhagen, Denmark. He has published 15 International books with repute publishers like BPB Publications, IGI Global, De Gruyter from India, Germany, USA, UK. He has made significant contributions to our society's technological transformation. He has several awards to his credit such as International travel grant for attending the IEEE Region 8 Committee Meeting at Warsaw, Poland; International travel grant for Germany from ITS Europe, Passau, Germany; Best Research Paper Award at the University of Gondar, Ethiopia; IEEE Liberia Subsection Founder Award; Gold Medal Award in MTech (Hons.); IEEE Ghana Section Award-Technical and Professional Activity Chair; IEEE Senior Member Recognition, Best IEEE Student Branch Award, Elsevier Reviewer Recognition Award. He has published 75 scientific research papers in SCI/Scopus/Web of Science and IEEE Transactions Journal, conferences, 2 Indian Patents, 1 Australian Patent Grants. He has made several international visits to Denmark, Sweden, Germany, Norway, Ghana, Liberia, Ethiopia, Russia, Dubai, Mexico, and Jordan for research exposures. His research interests focus on Artificial Intelligence, Cloud-edge computing, Machine-deep learning and Intelligent IoT.

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