Gespeichert in:
| Weitere beteiligte Personen: | , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Amsterdam
Elsevier
[2025]
|
| Schriftenreihe: | Earth observation series
|
| Schlagwörter: | |
| Links: | https://doi.org/10.1016/C2023-0-51018-3 https://doi.org/10.1016/C2023-0-51018-3 |
| Abstract: | Deep Learning for Earth Observation and Climate Monitoring bridges the gap between deep learning and the Earth sciences, offering cutting-edge techniques and applications that are transforming our understanding of the environment. With a focus on practical scenarios, this book introduces readers to the fundamental concepts of deep learning, from classification and image segmentation to anomaly detection and domain adaptability. The book includes practical discussion on regression, parameter retrieval, forecasting, and interpolation, among other topics. With a solid foundational theory, real-world examples, and example codes, it provides a full understanding of how intelligent systems can be applied to enhance Earth observation and especially climate monitoring. This book allows readers to apply learning representations, unsupervised deep learning, and physics-aware models to Earth observation data, enabling them to leverage the power of deep learning to fully utilize the wealth of environmental data from satellite technologies |
| Umfang: | 1 Online-Ressource |
| ISBN: | 9780443247132 |
| DOI: | 10.1016/C2023-0-51018-3 |
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| id | DE-604.BV050309413 |
| illustrated | Not Illustrated |
| indexdate | 2025-06-05T10:00:45Z |
| institution | BVB |
| isbn | 9780443247132 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-035642919 |
| oclc_num | 1513213260 |
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| publisher | Elsevier |
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| series2 | Earth observation series |
| spelling | Deep learning for Earth observation and climate monitoring edited by Uzair Aslam Bhatti, Mir Muhammad Nizamani, Yong Wang, Hao Tang Amsterdam Elsevier [2025] 1 Online-Ressource txt rdacontent c rdamedia cr rdacarrier Earth observation series Deep Learning for Earth Observation and Climate Monitoring bridges the gap between deep learning and the Earth sciences, offering cutting-edge techniques and applications that are transforming our understanding of the environment. With a focus on practical scenarios, this book introduces readers to the fundamental concepts of deep learning, from classification and image segmentation to anomaly detection and domain adaptability. The book includes practical discussion on regression, parameter retrieval, forecasting, and interpolation, among other topics. With a solid foundational theory, real-world examples, and example codes, it provides a full understanding of how intelligent systems can be applied to enhance Earth observation and especially climate monitoring. This book allows readers to apply learning representations, unsupervised deep learning, and physics-aware models to Earth observation data, enabling them to leverage the power of deep learning to fully utilize the wealth of environmental data from satellite technologies Deep learning (Machine learning) Earth sciences / Remote sensing Apprentissage profond Sciences de la terre / Télédétection Bhatti, Uzair Aslam edt Nizamani, Mir Muhammad edt Wang, Yong edt Tang, Hao edt Erscheint auch als Druck-Ausgabe, Paperback 978-0-443-24712-5 https://doi.org/10.1016/C2023-0-51018-3 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Deep learning for Earth observation and climate monitoring |
| title | Deep learning for Earth observation and climate monitoring |
| title_auth | Deep learning for Earth observation and climate monitoring |
| title_exact_search | Deep learning for Earth observation and climate monitoring |
| title_full | Deep learning for Earth observation and climate monitoring edited by Uzair Aslam Bhatti, Mir Muhammad Nizamani, Yong Wang, Hao Tang |
| title_fullStr | Deep learning for Earth observation and climate monitoring edited by Uzair Aslam Bhatti, Mir Muhammad Nizamani, Yong Wang, Hao Tang |
| title_full_unstemmed | Deep learning for Earth observation and climate monitoring edited by Uzair Aslam Bhatti, Mir Muhammad Nizamani, Yong Wang, Hao Tang |
| title_short | Deep learning for Earth observation and climate monitoring |
| title_sort | deep learning for earth observation and climate monitoring |
| url | https://doi.org/10.1016/C2023-0-51018-3 |
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