Semantic segmentation is an essential task in polarimetric synthetic aperture radar (PolSAR) image interpretation. To address the issue of insufficient measurement ability of single-view similarity, ...

DNGs are diverse network graphs with texts and different styles of nodes and edges, including mind maps, modeling graphs, and flowcharts. They are high-level visualizations that are easy for humans to ...

But once other factors increase, they can greatly affect the segmentation results. With the rise of deep neural networks, various neural network methods have been quickly applied to various image ...

To address these limitations, a team of researchers has introduced Semantic-SAM, a universal image segmentation model which segments and recognizes objects at any desired granularity based on user ...

Image segmentation is typically used to locate objects in images by marking their specific contours and the area inside those. In computer vision, semantic segmentation is referred as the task of ...

Therefore, the major issue addressed with such approach is the classification of integrated imagery on the image level. However, land cover classification is a problem of image segmentation, what to ...