Disaster Area Detection from Synthetic Aperture Radar Images Using Convolutional Autoencoder and One-class SVM
In recent years, research on detecting disaster areas from synthetic aperture radar (SAR) images has been conducted. When machine learning is used for disaster area detection, a large number of training data are required; however, we cannot obtain so much training data with correct class labels. The...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Atlantis Press
2019-06-01
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| Series: | Journal of Robotics, Networking and Artificial Life (JRNAL) |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/125909660/view |