Buch, Englisch, 255 Seiten, Format (B × H): 210 mm x 279 mm, Gewicht: 652 g
Buch, Englisch, 255 Seiten, Format (B × H): 210 mm x 279 mm, Gewicht: 652 g
Reihe: Advances in Science, Technology & Innovation
ISBN: 978-3-031-49485-7
Verlag: Springer International Publishing
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken
- Geowissenschaften Umweltwissenschaften Umweltwissenschaften
- Mathematik | Informatik Mathematik Mathematik Allgemein
- Naturwissenschaften Biowissenschaften Biowissenschaften Ökologie
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
Weitere Infos & Material
Abstract Frame Theory.- Fourier-type Frame Theory.- Bandlimited Framelet Theory.- Compactly Supported Framelet Theory.- Periodic Framelet Theory.- Spheroidal-type Frame Theory.- Big Data.- Climate Diagnosis.- Frame Neural Networks.