The intelligent segmentation of high-resolution remote sensing (HRS) image, also called as
dense prediction task for HRS image, has been and will continue to be important research in …

The advances in remote sensing sensors during the last two decades have led to the
production of very high spatial resolution multispectral images. In order to adapt to this rapid …

Remote sensing (RS) images enable high-resolution information collection from complex
ground objects and are increasingly utilized in the earth observation research. Recently, RS …

Image segmentation is a key technique involved in information extraction from high spatial
resolution remote sensing images. Studying the impact of the evaluation method on the …

Semantic segmentation is a crucial step in the intelligent interpretation of high-resolution
remote sensing images (HRSIs). Convolutional neural networks and transformers are widely …

Man-made objects, such as buildings and roads, which are important targets for information
extraction from high spatial resolution (HSR) remote sensing images, often feature straight …

Image segmentation, is of utmost importance in the disciplines of digital image processing,
particularly remote sensing and computer vision, has seen an increasing demand for …

Abstract Geographic Object-Based Image Analysis (GEOBIA) is a popular classification
approach for high spatial resolution (HSR) images in the remote sensing (RS) community. It …

Object-based image analysis (OBIA) has been widely adopted as a common paradigm to
deal with very high-resolution remote sensing images. Nevertheless, OBIA methods strongly …

Image segmentation has a remarkable influence on the classification accuracy of object-
based image analysis. Accordingly, how to raise the performance of remote sensing image …