Synthetic Aperture Radar (Sar) Data Applications (合成孔徑雷達數據應用)

Rysz, Maciej, Tsokas, Arsenios, Dipple, Kathleen M.

  • 出版商: Springer
  • 出版日期: 2024-01-20
  • 售價: $5,540
  • 貴賓價: 9.5$5,263
  • 語言: 英文
  • 頁數: 278
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3031212274
  • ISBN-13: 9783031212277
  • 海外代購書籍(需單獨結帳)

相關主題

商品描述

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 also included.


商品描述(中文翻譯)

這本精心策劃的書籍深入探討了合成孔徑雷達(Synthetic Aperture Radar, SAR)的多種應用,並呈現了最前沿的討論。該書整合了跨學科的科學,包含了新穎的想法、定量方法和研究成果,承諾能推進學術界和工業界的計算實踐與技術。SAR 應用採用了多樣且通常複雜的計算方法,這些方法根植於機器學習、估計、統計學習、反演模型和經驗模型。書中突顯了 SAR 數據在地球觀測、物體檢測與識別、變化檢測、導航和干擾緩解等當前及新興應用。書中還包括了尖端方法,特別強調機器學習。在 SAR 圖像中的物體檢測與識別中,考慮了當代深度學習模型及其相應的特徵提取和訓練方案。書中進一步比較和討論了 SAR 輔助導航中的最先進神經網絡架構。此外,還包括了在檢索陸地和海洋信息(如風、波浪、土壤條件等)方面的先進經驗和機器學習模型。

作者簡介

Maciej Rysz is currently an assistant professor at the Department of Information Systems & Analytics at the Farmer School of Business within Miami University. Prior to joining Miami University, he was a research assistant professor at the Industrial & Systems Engineering Department at the University of Florida and served as a postdoctoral research associate under the National Research Council of the National Academies. He received his Ph.D. in Industrial Engineering with emphasis on operations research from the University of Iowa in 2014. His research areas of interest include mathematical programming, machine learning, network science and encryption.
Arsenios Tsokas currently works as an analyst for Citibank, N.A. He received his B.Sc. in Mathematics from the Aristotle University of Thessaloniki in 2014. He received his Ph.D. degree in Industrial & Systems Engineering from the University of Florida in 2021. He has a diverse background including data science, optimization, and machine learning. He has worked on various topics, such as data analysis with applications in medicine and network science with applications on network robustness.
Kathleen M Dipple is currently a research scientist with the US Air Force Research Lab (AFRL). A first-generation undergraduate student, she earned her bachelor's degree in Chemistry from Appalachian State University and received her Ph.D. from the Nanoscale Science program at the University of North Carolina at Charlotte. She completed her post-doctoral work holding a provisional patent in the Nature-Inspired Section at AFRL's Munitions Directorate through the National Research Council Associateship Program.
Kaitlin Fair is a Systems Development Engineer working on guidance, navigation, and control technologies at the Air Force Life Cycle Management Center. Dr. Fair served as a Research Engineer and Team Lead at the Air Force Research Lab for ten years prior to serving in her current role, during which she received the SMART Scholarship and completed her PhD in Electrical Engineering from the Georgia Institute of Technology in 2017. Her research interests include efficient signal processing and algorithm development on brain-inspired (neuromorphic) engineering architectures.
Panos M. Pardalos is a distinguished Professor Emeritus of Industrial and Systems Engineering at the University of Florida. Additionally, he is the Paul and Heidi Brown Preeminent Professor in Industrial & Systems Engineering. He is also an affiliated faculty member of the Computer and Information Science Department, the Hellenic Studies Center, and the Biomedical Engineering Program. He is also the Director of the Center for Applied Optimization. Dr. Pardalos is a world leading expert in global and combinatorial optimization. His recent research interests include network design problems, optimization in telecommunications, e-commerce, data mining, biomedical applications, and massive computing. He has co-authored and co-edited more than 30 books, as well as publishing more than 600 journal articles and conference proceedings. Prof. Pardalos is a Fellow of AAAS (American Association for the Advancement of Science), Fellow of American Institute for Medical and Biological Engineering (AIMBE), and EUROPT. He is a Distinguished International Professor by the Chinese Minister of Education; Honorary Professor of Anhui University of Sciences and Technology, China; Elizabeth Wood Dunlevie Honors Term Professor; Honorary Doctor, V.M. Glushkov Institute of Cybernetics of The National Academy of Sciences of Ukraine; Foreign Associate Member of Reial Academia de Doctors, Spain; and Advisory board member of the Centre for Optimisation and Its Applications, Cardiff University, UK. He is also the recipient of UF 2009 International Educator Award; Medal (in recognition of broad contributions in science and engineering) of the University of Catani, Italy; EURO Gold Medal (EGM); Honorary Doctor of Science Degree, Wilfrid Laurier University, Canada; Senior Fulbright Specialist Award; University of Florida Research Foundation Professorship; and IBM Achievement Award.

作者簡介(中文翻譯)

Maciej Rysz 目前是邁阿密大學農夫商學院資訊系統與分析系的助理教授。在加入邁阿密大學之前,他曾擔任佛羅里達大學工業與系統工程系的研究助理教授,並在國家科學院的國家研究委員會擔任博士後研究助理。他於2014年在愛荷華大學獲得工業工程博士學位,專注於運籌學。他的研究興趣包括數學規劃、機器學習、網絡科學和加密技術。

Arsenios Tsokas 目前在花旗銀行擔任分析師。他於2014年在塞薩洛尼基亞里士多德大學獲得數學學士學位,並於2021年在佛羅里達大學獲得工業與系統工程博士學位。他擁有多元背景,包括數據科學、優化和機器學習。他曾在多個主題上工作,例如醫學應用的數據分析和網絡科學中網絡穩健性的應用。

Kathleen M Dipple 目前是美國空軍研究實驗室(AFRL)的研究科學家。作為第一代大學生,她在阿巴拉契亞州立大學獲得化學學士學位,並在北卡羅來納大學夏洛特分校的納米尺度科學計劃中獲得博士學位。她完成了博士後研究,並在AFRL的彈藥局的自然啟發部分持有一項臨時專利,這是通過國家研究委員會的博士後計劃獲得的。

Kaitlin Fair 是一名系統開發工程師,專注於空軍生命週期管理中心的導航、指導和控制技術。在擔任目前職位之前,Fair博士在空軍研究實驗室擔任研究工程師和團隊負責人十年,期間獲得了SMART獎學金,並於2017年在喬治亞理工學院獲得電機工程博士學位。她的研究興趣包括高效信號處理和基於大腦啟發的(神經形態)工程架構的算法開發。

Panos M. Pardalos 是佛羅里達大學工業與系統工程的傑出名譽教授。此外,他還是工業與系統工程的保羅與海蒂·布朗卓越教授。他同時是計算機與資訊科學系、希臘研究中心和生物醫學工程計劃的附屬教員,也是應用優化中心的主任。Pardalos博士是全球和組合優化的世界領先專家。他最近的研究興趣包括網絡設計問題、電信優化、電子商務、數據挖掘、生物醫學應用和大規模計算。他共同編著和編輯了30多本書籍,並發表了600多篇期刊文章和會議論文。Pardalos教授是美國科學促進會(AAAS)會士、美國醫療與生物工程學會(AIMBE)會士及EUROPT成員。他是中國教育部頒發的傑出國際教授;中國安徽科技大學榮譽教授;伊莉莎白·伍德·鄧勒維榮譽學期教授;烏克蘭國家科學院V.M. Glushkov網絡學院榮譽博士;西班牙Reial Academia de Doctors的外國成員;以及英國卡迪夫大學優化及其應用中心的顧問委員會成員。他還是2009年佛羅里達大學國際教育者獎的獲得者;意大利卡塔尼亞大學科學與工程廣泛貢獻獎勳章;EURO金獎(EGM)。