
Data-Driven Systems and Intelligent Applications
Description
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This book:
Discusses intelligent systems and cloud computing with the help of artificial intelligence and machine learning.
Showcases the importance of machine learning and deep learning in data-driven and cloud-based applications to improve their capabilities and intelligence.
Presents the latest developments in data-driven and cloud applications with respect to their design and architecture.
Covers artificial intelligence methods along with their experimental result analysis through data processing tools.
Presents the advent of machine learning, deep learning, and reinforcement technique for cloud computing to provide cost-effective and efficient services.
The text will be useful for senior undergraduate, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer engineering, manufacturing engineering, and production engineering.
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Persons
N. Krishna Chaitanya, currently working as a Professor in ECE at RSR Engineering College, Kavali and he has 20 years of teaching experience. He received his Ph.D degree from JNT University Kakinada, India. He has published more than 65 articles in reputed International Journals, book chapters and international conferences. He authored 4 text books and 2 patent grants. He is a reviewer, Associate Editor and editor for Scopus Journals and SCI journals like Springer, Elsevier, IGI Global, and Wiley. He attended more than 25 workshops/training programs. He is a member in various technical forums like ISTE, IAENG, SCIEI, IACSIT and SDIWC. He guided more than 30 PG and 60 UG projects. His research areas include Computer Networks, Internet of Things, Wireless Communication, Network security and Image Processing. He taught subjects like Software Engineering, Data Security, Computer networks, Wireless communications, Electronic devices and circuits, Electronic circuit analysis etc.
Pradeep N is working as Professor in Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Davangere, Karnataka, India affiliated Visvesvaraya Technological University, Belagavi, Karnataka, India. He is having 18 years of academic experience, which includes teaching and research experience. He has worked at various verticals starting from Lecturer to Associate Professor. He has been appointed as Senior Member, Iranian Neuroscience Society-FARS Chapter (SM-FINSS) for a duration of TWO years (March 1st 2021 to March 2nd 2023). He has honoured with Hon. D.Eng (Honorary Doctrine Engineering) (Honoris Causa), Iranian Neuroscience Society FARS chapter and Dana Brain Health Institute, Shiraz, Iran in 2021. He has completed Short Term Post-PhD Pilot Research Project 2021 at THU DAO MOT university, Vietnam. His research areas of interest include Machine Learning, Pattern Recognition, Medical Image Analysis, Knowledge Discovery Techniques, and Data Analytics. He is presently guiding TWO research scholars on Knowledge Discovery and Medical Image Analysis. He has successfully edited books published by reputed international publishers. He has published more than 20 research articles published in refereed journals and also authored SIX book chapters. He is a reviewer of various International Conferences and few journals which includes Multimedia Tools and Applications, Springer. His one Indian Patent application is published and one Australian Patent is granted and also, he is successful in getting SIX copyright grants for his novel work. He taught subjects like artificial intelligence, Software Engineering, Cloud Computing, Storage Area Networks, Pattern Recognition etc. He is a Professional member in IEEE, ACM, ISTE and IEI. Also, he is a Technical Committee Member for Davangere Smart City, Davangere.
Harish Garg is working as an Associate Professor at Thapar Institute of Engineering & Technology, Deemed University, Patiala, Punjab, India. His research interests include Computational Intelligence, Reliability analysis, Multi-criteria decision making, Evolutionary algorithms, Expert systems and decision support systems, Computing with words and Soft Computing. He has authored more than 358 papers (over 307 are SCI) published in refereed International Journals including Information Sciences, IEEE Transactions on Fuzzy Systems, Applied Intelligence, Expert Systems with Applications, Applied Soft Computing, IEEE Access, International Journal of Intelligent Systems, Computers and Industrial Engineering, Cognitive Computations, Soft Computing, Artificial Intelligence Review, IEEE/CAA Journal of Automatic Sinica, IEEE Transactions on Emerging Topics in Computational Intelligence, Computers & Operations Research, Measurement, Journal of Intelligent & Fuzzy Systems, International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, and many more. He has also authored seven book chapters. His Google citations are over 14330+. He is the recipient of the Top-Cited Paper by India-based Author (2015 - 2019) from Elsevier Publisher. Dr. Garg is the Editor-in-Chief of Journal of Computational and Cognitive Engineering; Annals of Optimization Theory and Practice. He is also the Associate Editors for Soft Computing, Alexandria Engineering Journal, Journal of Intelligent & Fuzzy Systems, Kybernetes, Complex and Intelligent Systems, Journal of Industrial & Management Optimization,Technological and Economic Development of Economy, International Journal of Computational Intelligence Systems, CAAI Transactions on Intelligence Technology, Mathematical Problems in Engineering, Complexity, etc.
Alessandro Bruno is a Lecturer in Computing at Bournemouth University's Department of Computing and Informatics. HE received his Master Degree in Computer Engineering in 2008 with a thesis on Biomedical Imaging. On March 1st of 2009, He started his PhD scholarship in Computer Engineering at DINFO (Computer Engineering Department) at Palermo University. In April 2012, he defended his PhD thesis, which was focused on the analysis of Local Keypoints and Texture for advanced image investigations. From July 2012 up to July 2014, he won a position as a postdoctoral research fellow at Palermo University, focusing on Image Forensics, Object Recognition and Visual Perception. From January 2015 until June 2015, He worked as a Software Engineer at the IZS (Istituto Zooprofilattico Sperimentale della Sicilia) over a project that involved optimising oil and flour tracking from the producer down to the consumer using software engineering techniques. From January 2016 until January 2017, he worked at Palermo University as a postdoctoral research fellow. Alessandro Bruno's main research interests focus on Computer Vision, Artificial Intelligence and Image Analysis. He has mostly dealt with Visual Attention and Visual Saliency, Biomedical Imaging, Crowd Behaviour Analysis, Image and Video Forensics, Remote Sensing and Human-Computer Interaction. He also works on deep learning solutions applied to image generation from different application domains.
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