An Efficient Change Detection for Large SAR Images Based on Modified U-Net Framework
Large SAR images usually contain a variety of land-cover types and accordingly complicated change types, which cause great difficulty for accurate change detection. The U-Net is a special fully convolutional neural network that not only can capture multiple features in the image context but also ena...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2020-05-01
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| Series: | Canadian Journal of Remote Sensing |
| Online Access: | http://dx.doi.org/10.1080/07038992.2020.1783993 |