Overview
Demystifies computational intelligence for those working outside of engineering and computer science
Introduces cross-disciplinary platforms and dialog
Emphasizes modularity for enhancing computational intelligence frameworks
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Table of contents (15 chapters)
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Front Matter
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A Panorama of Computational Intelligence in Super-Resolution Imaging
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Front Matter
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State-of-the-Art Computational Intelligence in Super-Resolution Imaging
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Front Matter
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Back Matter
Keywords
About this book
This book explores the application of deep learning techniques within a particularly difficult computational type of computer vision (CV) problem ─ super-resolution (SR). The authors present and discuss ways to apply computational intelligence (CI) methods to SR. The volume also explores the possibility of using different kinds of CV techniques to develop and enhance the tools/processes related to SR. The application areas covered include biomedical engineering, healthcare applications, medicine, histology, and material science. The book will be a valuable reference for anyone concerned with multiple multimodal images, especially professionals working in remote sensing, nanotechnology and immunology at research institutes, healthcare facilities, biotechnology institutions, agribusiness services, veterinary facilities, and universities.
Editors and Affiliations
About the editors
Anand Deshpande is currently serving as the Principal and Director of the Angadi Institute of Technology and Management (AITM), India. He received his PhD in Electronics and Communication and a Master of Technology degree in Digital Communication and Networking from Visvesvaraya Technological University, and a Bachelor of Engineering degree in Electronics and Communication Engineering from Karnatak University, Dharwad. His research work has been published in international journals, international conferences, and books, and he has filed patents in several areas. Dr. Deshpande is a reviewer for a number of journals published by the IEEE, The Institution of Engineering and Technology (IET), and Springer. His research interests include artificial intelligence, image and video analytics, data analytics, and machine vision.
Vania Vieira Estrela is currently a member of the faculty in the Department of Telecommunications at Federal Fluminense University (UFF), Brazil. Professor Estrela obtained her BSc degree in Electrical and Computer Engineering (ECE) from Federal University of Rio de Janeiro (UFRJ), an MSc in ECE from the Technological Institute of Aeronautics (ITA) and Northwestern University, and her PhD in ECE from the Illinois Institute of Technology (IIT). She has taught at DeVry University, State University of Northern Rio de Janeiro (UENF), and the West Zone State University, Brazil. Her research interests include signal/image/video processing, inverse problems, computational and mathematical modeling, stochastic models, multimedia, electronic instrumentation, computational intelligence, automated vehicles, machine learning, and remote sensing. She is an Editor for the International Journal of Ambient Computing and Intelligence, International Journal on Computational Science & Applications, and the EURASIP Journal on Advances in Signal Processing, and a member of the IEEE and the Association for Computing Machinery (ACM).Navid Razmjooy holds a PhD in Electrical Engineering (Control and Automation) from Tafresh University, an MSc with honors in Mechatronics Engineering from the Isfahan Branch of Islamic Azad University (IAU), and a BSc from the Ardabil Branch of IAU. His research interests include renewable energies, control, interval analysis, optimization, image processing, machine vision, soft computing, data mining, evolutionary algorithms, and system control. He is a senior member of the IEEE and Young Researchers Club of IAU. Dr. Razmjooy has published five books and more than 120 papers in English and Farsi in peer-reviewed journals and conferences. He is a reviewer for several national and international journals and conferences.
Bibliographic Information
Book Title: Computational Intelligence Methods for Super-Resolution in Image Processing Applications
Editors: Anand Deshpande, Vania V. Estrela, Navid Razmjooy
DOI: https://doi.org/10.1007/978-3-030-67921-7
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-67920-0Published: 29 May 2021
Softcover ISBN: 978-3-030-67923-1Published: 30 May 2022
eBook ISBN: 978-3-030-67921-7Published: 28 May 2021
Edition Number: 1
Number of Pages: XIV, 305
Number of Illustrations: 45 b/w illustrations, 110 illustrations in colour
Topics: Computational Intelligence, Biomedical Engineering and Bioengineering, Nanotechnology and Microengineering, Image Processing and Computer Vision, Artificial Intelligence