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Original paper

DABNet: Deformable Contextual and Boundary-Weighted Network for Cloud Detection in Remote Sensing Images

Volume: 60, Pages: 1 - 16
Published: Jan 5, 2021
Abstract
In recent years, deep convolutional neural networks (DCNNs) have made significant progress in cloud detection tasks, and the detection accuracy has been greatly improved. However, most existing CNN-based models have high computational complexity, which limits their practical application, especially for spaceborne optical remote sensing. In addition, most of the methods cannot make adaptive adjustments based on the structural information of the...
Paper Details
Title
DABNet: Deformable Contextual and Boundary-Weighted Network for Cloud Detection in Remote Sensing Images
Published Date
Jan 5, 2021
Volume
60
Pages
1 - 16
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