| 書目名稱 | Frame Theory in Data Science | | 編輯 | Zhihua Zhang,Palle E. T. Jorgensen | | 視頻video | http://file.papertrans.cn/348/347605/347605.mp4 | | 概述 | The internationally first book on systematic frame theory and algorithms.Novel applications of frame theory in big data, deep learning and climate diagnosis & prediction.Includes the authors‘ frame re | | 叢書名稱 | Advances in Science, Technology & Innovation | | 圖書封面 |  | | 描述 | This book establishes brand-new frame theory and technical implementation in data science, with a special focus on spatial-scale feature extraction, network dynamics, object-oriented analysis, data-driven environmental prediction, and climate diagnosis. Given that data science is unanimously recognized as a core driver for achieving Sustainable Development Goals of the United Nations, these frame techniques bring fundamental changes to multi-channel data mining systems and support the development of digital Earth platforms. This book integrates the authors‘ frame research in the past twenty years and provides cutting-edge techniques and depth for scientists, professionals, and graduate students in data science, applied mathematics, environmental science, and geoscience.? | | 出版日期 | Book 2024 | | 關(guān)鍵詞 | Frame Theory; Framelets; Frame network; Data mining; Object-oriented data analysis; Climate diagnosis; Env | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-49483-3 | | isbn_softcover | 978-3-031-49485-7 | | isbn_ebook | 978-3-031-49483-3Series ISSN 2522-8714 Series E-ISSN 2522-8722 | | issn_series | 2522-8714 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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