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1. |
Record Nr. |
UNINA9910133326503321 |
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Titolo |
Annual report to Congress fiscal year ... pursuant to subsection (j) of Section 7A of the Clayton Act, Hart-Scott-Rodino Antitrust Improvements Act of 1976 |
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Pubbl/distr/stampa |
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Federal Trade Commission, Bureau of Competition |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Periodico |
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2. |
Record Nr. |
UNINA9910367564103321 |
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Autore |
Jung Hyung-Sup |
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Titolo |
Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing / Hyung-Sup Jung, Saro Lee |
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Pubbl/distr/stampa |
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MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
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Basel, Switzerland : , : MDPI, , 2019 |
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ISBN |
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Descrizione fisica |
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1 electronic resource (438 p.) |
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Soggetti |
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Pharmaceutical chemistry and technology |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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As computer and space technologies have been developed, geoscience information systems (GIS) and remote sensing (RS) technologies, which deal with the geospatial information, have been rapidly maturing. Moreover, over the last few decades, machine learning techniques including artificial neural network (ANN), deep learning, decision tree, and support vector machine (SVM) have been successfully applied to geospatial science and engineering research fields. The machine learning techniques have been widely applied to GIS and RS research |
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fields and have recently produced valuable results in the areas of geoscience, environment, natural hazards, and natural resources. This book is a collection representing novel contributions detailing machine learning techniques as applied to geoscience information systems and remote sensing. |
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