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Lizhe Wang
Remote Sensing Intelligent Interpretation for Geology
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4570601Remote Sensing Intelligent Interpretation for Geologyhttps://www.gandhi.com.mx/remote-sensing-intelligent-interpretation-for-geology-9789819989973/phttps://gandhi.vtexassets.com/arquivos/ids/4246280/image.jpg?v=63844655262530000033173686MXNSpringer Nature SingaporeInStock/Ebooks/<p>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.</p><p>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.</p><p>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.</p>...4377743Remote Sensing Intelligent Interpretation for Geology33173686https://www.gandhi.com.mx/remote-sensing-intelligent-interpretation-for-geology-9789819989973/phttps://gandhi.vtexassets.com/arquivos/ids/4246280/image.jpg?v=638446552625300000InStockMXN99999DIEbook20249789819989973_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_<p>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.</p><p>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.</p><p>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.</p>...9789819989973_Springer Nature Singaporelibro_electonico_9789819989973_9789819989973Lizhe WangInglésMéxico2024-01-03T00:00:00+00:00Springer Nature Singapore