| 书目名称 | Frame Theory in Data Science |
| 编辑 | Zhihua Zhang,Palle E. T. Jorgensen |
| 视频video | |
| 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 |
| 丛书名称 | Advances in Science, Technology & Innovation |
| 图书封面 |  |
| 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 |
| 关键词 | 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 |
发表于 2025-3-21 20:01:53
