Applications of Hybrid Metaheuristic Algorithms for Image Processing /
This book presents a collection of the most recent hybrid methods for image processing. The algorithms included consider evolutionary, swarm, machine learning and deep learning. The respective chapters explore different areas of image processing, from image segmentation to the recognition of objects...
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| Other Authors: | , |
| Format: | eBook |
| Language: | English |
| Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2020.
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| Edition: | 1st ed. 2020. |
| Series: | Studies in Computational Intelligence,
890 |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | This book presents a collection of the most recent hybrid methods for image processing. The algorithms included consider evolutionary, swarm, machine learning and deep learning. The respective chapters explore different areas of image processing, from image segmentation to the recognition of objects using complex approaches and medical applications. The book also discusses the theory of the methodologies used to provide an overview of the applications of these tools in image processing. The book is primarily intended for undergraduate and postgraduate students of science, engineering and computational mathematics, and can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence. Further, it is a valuable resource for researchers from the evolutionary computation, artificial intelligence and image processing communities. |
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| Physical Description: | 1 online resource (IX, 490 pages 313 illustrations, 221 illustrations in color.) |
| ISBN: | 9783030409777 |
| ISSN: | 1860-9503 ; |
| DOI: | 10.1007/978-3-030-40977-7 |