Due to its wide applications, remote sensing (RS) image semantic segmentation has
attracted increasing research interest in recent years. Benefiting from its hierarchical abstract …

Cross-domain scene classification refers to the scene classification task in which the training
set (termed source domain) and the test set (termed target domain) come from different …

The scene classification of high spatial resolution (HSR) imagery involves labeling an HSR
image with a specific high-level semantic class according to the composition of the semantic …

Providing an accurate evaluation of palm tree plantation in a large region can bring
meaningful impacts in both economic and ecological aspects. However, the enormous …

With the development of convolutional neural networks (CNNs), the semantic understanding
of remote sensing (RS) scenes has been significantly improved based on their prominent …

Purpose The new challenge in Artificial Intelligence (AI) is to understand the limitations of
models to reduce potential harm. Particularly, unknown disparities based on demographic …

Although domain adaptation approaches have been proposed to tackle cross-regional,
multitemporal, and multisensor remote sensing applications since they do not require any …

Most deep metric learning-based image characterization methods exploit supervised
information to model the semantic relations among the remote sensing (RS) scenes …

Scene classification of high-resolution remote sensing images (HRRSI) is one of the most
important means of land-cover classification. Deep learning techniques, especially the …

Remote sensing image scene classification aims to automatically assign semantic labels for
remote sensing images. Recently, to overcome the distribution discrepancy of training data …