Applications of Artificial Intelligence and Machine Learning: Select Proceedings of ICAAAIML 2020: Lecture Notes in Electrical Engineering, cartea 778
Editat de Ankur Choudhary, Arun Prakash Agrawal, Rajasvaran Logeswaran, Bhuvan Unhelkaren Limba Engleză Paperback – 29 iul 2022
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Specificații
ISBN-13: 9789811630699
ISBN-10: 9811630690
Ilustrații: XVI, 738 p. 326 illus., 247 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 1.04 kg
Ediția:1st ed. 2021
Editura: Springer Nature Singapore
Colecția Springer
Seria Lecture Notes in Electrical Engineering
Locul publicării:Singapore, Singapore
ISBN-10: 9811630690
Ilustrații: XVI, 738 p. 326 illus., 247 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 1.04 kg
Ediția:1st ed. 2021
Editura: Springer Nature Singapore
Colecția Springer
Seria Lecture Notes in Electrical Engineering
Locul publicării:Singapore, Singapore
Cuprins
Chapter 1: Building a Language Data Set in Telugu Using Machine Learning Techniques to Address Suicidal Ideation and Behaviors in Adolescents.- Chapter 2: Feature Selection and Performance Comparison of Various Machine Learning Classifiers for Analyzing Students’ Performance Using Rapid Miner.- Chapter 3: Internet of Things (IoT) Based Automated Light Intensity Model using NodeMcu ESP 8266 Microcontroller.- Chapter 4: Handwritten Mathematical Symbols Classification Using WEKA.- Chapter 5: Enhancing Socio-Cultural Learning Using Hyperlocal Experience.- Chapter 6: Subsequent Technologies behind IoT and its Development Roadmap Towards Integrated Healthcare Prototype Models.- Chapter 7: Bug Assignment- Utilization of Metadata Features along with Feature Selection and Classifiers.
Notă biografică
Ankur Choudhary is a Professor of the Department of Computer Science and Engineering at Sharda University, India. He completed his Ph.D. from Gautam Buddha University (GBU), India. His areas of research are nature-inspired optimization, artificial intelligence, software engineering, medical image processing, and digital watermarking. Dr. Choudhary has over 15 years of academic and research experience. He has published several research papers in conferences and journals. He is associated with various International Journals as a reviewer and editorial board member.
Arun Prakash Agrawal is currently a Professor with the Department of Computer Science and Engineering at Sharda University, India. He obtained his Masters and Ph.D. in Computer Science and Engineering from Guru Gobind Singh Indraprastha University, New Delhi, India. He has several research papers to his credit in refereed journals and conferences of international repute. He has also taught short-term courses at the Swinburne University of Technology, Melbourne, Australia, and Amity Global Business School, Singapore. His research interests include machine learning, software testing, artificial intelligence, and soft computing. He is an active professional member of the IEEE and ACM.
Rajasvaran Logeswaran is Head of the Asia Pacific Centre for Analytics and full Professor of Computing and Engineering at Asia Pacific University of Technology and Innovation (APU), Malaysia. He got his B.E. (Hons) Computing at Imperial College London, the United Kingdom. He completed his Masters and Ph.D. from Multimedia University, Malaysia and post-doctoral research in Korea. His research interest areas are image processing, data compression, neural networks, and data science. Dr. Logeswaran has over 150 publications in books, peer-reviewed journals, and international conference proceedings to his credit. Prof. Logeswaran has been a recipient of several scholarships and awards. He is a Senior Member of the IEEE and Chair of the award-winning IEEE Signal Processing Society Malaysia Chapter.
Bhuvan Unhelkar (BE, MDBA, MSc, Ph.D.) is an accomplished IT professional and Professor of IT at the University of South Florida at their Sarasota-Manatee campus. He is also Founding Consultant at MethodScience and PlatiFi, with mastery in business analysis & requirements modeling, software engineering, big data strategies, agile processes, mobile business, and green IT. He has a Doctorate in the area of “Object Orientation” from the University of Technology, Sydney, in 1997. His areas of expertise include big data strategies, agile processes, business analysis & requirements modeling, corporate agile development, and quality assurance & testing. His industry experience includes banking, finance, insurance, government, and telecommunications where he develops and applies industry-specific process maps, business transformation approaches, capability enhancement, and quality strategies. Dr. Unhelkar has authored numerous executive reports, journal articles, and 20 books with internationally reputed publishers.
Arun Prakash Agrawal is currently a Professor with the Department of Computer Science and Engineering at Sharda University, India. He obtained his Masters and Ph.D. in Computer Science and Engineering from Guru Gobind Singh Indraprastha University, New Delhi, India. He has several research papers to his credit in refereed journals and conferences of international repute. He has also taught short-term courses at the Swinburne University of Technology, Melbourne, Australia, and Amity Global Business School, Singapore. His research interests include machine learning, software testing, artificial intelligence, and soft computing. He is an active professional member of the IEEE and ACM.
Rajasvaran Logeswaran is Head of the Asia Pacific Centre for Analytics and full Professor of Computing and Engineering at Asia Pacific University of Technology and Innovation (APU), Malaysia. He got his B.E. (Hons) Computing at Imperial College London, the United Kingdom. He completed his Masters and Ph.D. from Multimedia University, Malaysia and post-doctoral research in Korea. His research interest areas are image processing, data compression, neural networks, and data science. Dr. Logeswaran has over 150 publications in books, peer-reviewed journals, and international conference proceedings to his credit. Prof. Logeswaran has been a recipient of several scholarships and awards. He is a Senior Member of the IEEE and Chair of the award-winning IEEE Signal Processing Society Malaysia Chapter.
Bhuvan Unhelkar (BE, MDBA, MSc, Ph.D.) is an accomplished IT professional and Professor of IT at the University of South Florida at their Sarasota-Manatee campus. He is also Founding Consultant at MethodScience and PlatiFi, with mastery in business analysis & requirements modeling, software engineering, big data strategies, agile processes, mobile business, and green IT. He has a Doctorate in the area of “Object Orientation” from the University of Technology, Sydney, in 1997. His areas of expertise include big data strategies, agile processes, business analysis & requirements modeling, corporate agile development, and quality assurance & testing. His industry experience includes banking, finance, insurance, government, and telecommunications where he develops and applies industry-specific process maps, business transformation approaches, capability enhancement, and quality strategies. Dr. Unhelkar has authored numerous executive reports, journal articles, and 20 books with internationally reputed publishers.
Textul de pe ultima copertă
The book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning - ICAAAIML 2020. The book covers research in the areas of artificial intelligence, machine learning, and deep learning applications in healthcare, agriculture, business and security. This volume contains research papers from academicians, researchers as well as students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor network, sensors and sensor nodes, software engineering, and image processing. This book will be a valuable resource for students, academics and practitioners in industry working on AI applications.
Caracteristici
Covers research in the areas of artificial intelligence, machine learning, and deep learning applications Focuses on all aspects of engineering applications of artificial intelligence and machine learning in healthcare, agriculture, business and security Valuable resource for students, academics and practitioners in industry working on AI applications