… attentive high-resolution network, abbreviated as WaterHRNet, for extracting water bodies
from remote sensing imagery. First, … enhancement of category-attentive feature semantics, the …

… attentive refinement network (DARNet) to improve change detection on bitemporal very-high-resolution
remote sensing images… architecture with the Siamese network as a feature …

… -scale image pairs for uniform and nonuniform hazy images. This two-stage network, when
… the synthetic data sets and real-world images with more visually pleasing dehazed results. …

… the input images and the corresponding haze-free image, … To better handle non-uniform
hazy remote sensing images, … hazy image, and is subsequently utilized as the input of the …

… To predict pixel-level labels of remote sensing images, we apply the well-trained
attentive network on patches cropped from images using a sliding window of size 256 × 256, …

… Abstract—Change detection in remote sensing images is a chal- … To address these challenges,
this article introduces a novel maskguided local–global attentive network (MLA-Net). The …

… Attentive Bilateral Contextual Network (ABCNet) to realize efficient semantic segmentation of
fine-resolution remote sensing images… fine-resolution remotely sensed imagery, ie, ABCNet …

… for natural and synthetic images and remote sensing images. To address the … attentive
changes-to-captions network, called Chg2Cap for short, for bitemporal remote sensing images…

… In this paper, an effective remote sensing image change detection network named ADHR-CDNet
is proposed. A high resolution backbone based on HRNet is designed to obtain multi-…

… sensing imagery is a fundamental task in intelligent interpretation. Since deep convolutional
neural networks (… the DCNN-based model to remote sensing data analysis. However, the …