Computational Intelligence Methods for Super-Resolution in Image Processing Applications
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 possibi...
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| Other Authors: | , , |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2021.
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| Edition: | 1st ed. 2021. |
| Subjects: | |
| Online Access: | Full text (Wentworth users only) |
| Summary: | 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. 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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| Physical Description: | XIV, 305 pages 155 illustrations, 110 illustrations in color : online resource. |
| ISBN: | 9783030679217 |
| DOI: | 10.1007/978-3-030-67921-7 |