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Item #:
268183059
Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing (Paperback)
Item #:
268183059
€ 92
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Machine learning techniques have been successfully applied to geospatial science and engineering research fields, producing valuable results in geoscience, environment, natural hazards, and natural resources.
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Product Details
- 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.
| Manual & guide type | Instruction Manual |
| Book format | Paperback |
| Pages | 438 |
| Language | English |
| Brand | Saro Lee; Hyung-Sup Jung |
| Author | Saro Lee; Hyung-Sup Jung |
| Genre | Nonfiction |
| Bisac subject heading | Technology & Engineering |
| Dimensions | 9.00 x 6.00 x 1.50 in (22.9 x 15.2 x 3.8 cm) |
| Original languages | English |
Product Description
Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing (Paperback)
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Features & Benefits
- Learn about cutting-edge machine learning applications in geoscience.
- Explore novel contributions to GIS and remote sensing technologies.
- Discover valuable results from machine learning in environment and natural resources.
- Understand the integration of advanced techniques like ANN and deep learning.
- Enhance your knowledge in decision trees and support vector machines for geospatial analysis.
- Perfect for researchers and professionals in the field of geoscience.
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