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Found 4 papers, 1 papers with code
Samba: Semantic Segmentation of Remotely Sensed Images with State Space Model
The results reveal that Samba achieved unparalleled performance on commonly used remote sensing datasets for semantic segmentation.
SDRCNN: A single-scale dense residual connected convolutional neural network for pansharpening
Pansharpening is a process of fusing a high spatial resolution panchromatic image and a low spatial resolution multispectral image to create a high-resolution multispectral image.
OSTA: One-shot Task-adaptive Channel Selection for Semantic Segmentation of Multichannel Images
In this study, the concept of pruning from a supernet is used for the first time to integrate the selection of channel combination and the training of a semantic segmentation network.
SBSS: Stacking-Based Semantic Segmentation Framework for Very High Resolution Remote Sensing Image
However, it was found in this study that different classes of objects had their preferred resizing scale for more accurate semantic segmentation.
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