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Feature Aggregation Network for Building Extraction from High-resolution Remote Sensing Images
In this work, we propose the Feature Aggregation Network (FANet), concentrating on extracting both global and local features, thereby enabling the refined extraction of landmark buildings from high-resolution satellite remote sensing imagery.
FLDNet: A Foreground-Aware Network for Polyp Segmentation Leveraging Long-Distance Dependencies
On the high-level features, the local context module obtains the local characteristics related to the polyps by constructing different local context information.
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