| 书目名称 | Synthetic Aperture Radar (SAR) Data Applications | | 编辑 | Maciej Rysz,Arsenios Tsokas,Panos M. Pardalos | | 视频video | http://file.papertrans.cn/885/884329/884329.mp4 | | 概述 | Provides a cohesive overview of state-of-the-art data-driven computational methods using SAR data.Uses and tools employing ML, AI, SL and inversion methods in a series of SAR data applications.Current | | 丛书名称 | Springer Optimization and Its Applications | | 图书封面 |  | | 描述 | .This carefully curated volume presents an in-depth, state-of-the-art discussion on many applications of Synthetic Aperture Radar (SAR). Integrating interdisciplinary sciences, the book features novel ideas, quantitative methods, and research results, promising to advance computational practices and technologies within the academic and industrial communities. SAR applications employ diverse and often complex computational methods rooted in machine learning, estimation, statistical learning, inversion models, and empirical models. Current and emerging applications of SAR data for earth observation, object detection and recognition, change detection, navigation, and interference mitigation are highlighted. Cutting edge methods, with particular emphasis on machine learning, are included. Contemporary deep learning models in object detection and recognition in SAR imagery with corresponding feature extraction and training schemes are considered. State-of-the-art neural network architectures in SAR-aided navigation are compared and discussed further. Advanced empirical and machine learning models in retrieving land and ocean information — wind, wave, soil conditions, among others, are | | 出版日期 | Book 2022 | | 关键词 | synthetic aperture radar; SAR; land cover classification; forestation monitoring; biomass estimation; oce | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-21225-3 | | isbn_softcover | 978-3-031-21227-7 | | isbn_ebook | 978-3-031-21225-3Series ISSN 1931-6828 Series E-ISSN 1931-6836 | | issn_series | 1931-6828 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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