Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing
Overview & Synopsis
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 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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Document Information
| Document Title | Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing |
|---|---|
| Author / Organization | Lee, Saro, Jung, Hyung-Sup |
| Subject & Discipline | TJ1-1570 |
| Categories | Open Access Books |
| Publication Year | 2021 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
Directory of Open Access Books
(www.doabooks.org)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-109320 |
| Original Source Link | Visit Source Page on www.doabooks.org » |