Rotation-Invariant Feature Learning for Object Detection in VHR Optical Remote Sensing Images by Double-Net
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DOI: 10.1109/access.2019.2960931
Abstract: Rotation-invariant feature extraction is crucial for object detection in Very High Resolution (VHR) optical remote sensing images. Although convolutional neural networks (CNNs) are good at extracting the translation-invariant features and have been widely applied in… read more here.
Keywords: remote sensing; vhr optical; rotation; rotation invariant ... See more keywords