Remote Sensing Intelligent Interpretation for Geology
From Perspective of Geological Exploration
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Beschreibung
This book presents the theories and methods for geology intelligent interpretation based on deep learning and remote sensing technologies. The main research subjects of this book include lithology and mineral abundance.
This book focuses on the following five aspects: 1. Construction of geology remote sensing datasets from multi-level (pixel-level, scene-level, semantic segmentation-level, prior knowledge-assisted, transfer learning dataset), which are the basis of geology interpretation based on deep learning. 2. Research on lithology scene classification based on deep learning, prior knowledge, and remote sensing. 3. Research on lithology semantic segmentation based on deep learning and remote sensing. 4. Research on lithology classification based on transfer learning and remote sensing. 5. Research on inversion of mineral abundance based on the sparse unmixing theory and hyperspectral remote sensing.
The book is intended for undergraduate and graduate students who are interested in geology, remote sensing, and artificial intelligence. It is also used as a reference book for scientific and technological personnel of geological exploration.
This book presents the theories and methods for geology intelligent interpretation based on deep learning and remote sensing technologies. The main research subjects of this book include lithology and mineral abundance.
This book focuses on the following five aspects: 1. Construction of geology remote sensing datasets from multi-level (pixel-level, scene-level, semantic segmentation-level, prior knowledge-assisted, transfer learning dataset), which are the basis of geology interpretation based on deep learning. 2. Research on lithology scene classification based on deep learning, prior knowledge, and remote sensing. 3. Research on lithology semantic segmentation based on deep learning and remote sensing. 4. Research on lithology classification based on transfer learning and remote sensing. 5. Research on inversion of mineral abundance based on the sparse unmixing theory and hyperspectral remote sensing.
The book is intended for undergraduate and graduate students who are interested in geology, remote sensing, and artificial intelligence. It is also used as a reference book for scientific and technological personnel of geological exploration.
Presents interpretable intelligence interpretation theory on remote sensing geology Constructs geological remote sensing datasets from multi-level as a basis for intelligent interpretation Presents novel deep learning, prior knowledge, and transfer learning-based methods on geology interpretation
Autor*in
Weitao Chen
Themen in »Remote Sensing Intelligent Interpretation for Geology«
Geological exploration multimodal remote sensing Geology intelligent interpretation Interpretable deep learning Transfer learning Lithology scene and segmentation classification Mineral abundance inversion Fracture tectonic identification