Change detection based on remote sensing images plays an important role in the field of
remote sensing analysis, and it has been widely used in many areas, such as resources …

Remote sensing technology has undeniable importance in various industrial applications,
such as mineral exploration, plant detection, defect detection in aerospace and shipbuilding …

To better understand scene images in the field of remote sensing, multi-label annotation of
scene images is necessary. Moreover, to enhance the performance of deep learning models …

The urban functional zone, as a special fundamental unit of the city, helps to understand the
complex interaction between human space activities and environmental changes. Based on …

Remote sensing image scene classification is a challenging task. With the development of
deep learning, methods based on convolutional neural networks (CNNs) have made great …

Rapid and accurate extraction of water bodies from high-spatial-resolution remote sensing
images is of great value for water resource management, water quality monitoring and …

Abstract The Extraction of Roads from Remote Sensing Imagery is a rapidly developing field
that has significant impacts on both the economic and social domains. In the fields of urban …

The semantic segmentation of high-resolution (HR) remote sensing images (RSIs) has been
extensively researched in various applications. However, segmentation networks are prone …

As the basic spatial unit of urban planning and management, it is necessary to know the
distribution status of urban functional areas in time. Due to the complexity of urban land use …

Although many machine learning methods have been successfully applied for the object-
based classification of high resolution (HR) remote sensing imagery, current methods are …