Fuzzy machine learning algorithms for remote sensing image classification /
"This book covers the state of art image classification methods for discrimination of earth objects from remote sensing satellite data with an emphasis on fuzzy based learning methods including applications for preparing land cover classification outputs from actual satellite data. It provides...
| Main Authors: | , , |
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| Corporate Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
Boca Raton :
CRC Press/Taylor & Francis Group,
2020.
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| Edition: | First edition. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | "This book covers the state of art image classification methods for discrimination of earth objects from remote sensing satellite data with an emphasis on fuzzy based learning methods including applications for preparing land cover classification outputs from actual satellite data. It provides details about the temporal indices database using proposed class-based sensor independent approach supported by practical examples. Fuzzy based algorithms with machine learning algorithms to prepare land cover maps is discussed. Accuracy assessment for soft classification outputs are included and all algorithms are supported by in-house developed tool as Sub-pixel Multi-spectral Image Classifier"-- |
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| Physical Description: | 1 online resource (xxv, 192 pages) : illustrations |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9780429340369 0429340362 9781000091540 1000091546 9781000091526 100009152X 9781000091533 1000091538 |