[HTML][HTML] Deep learning in multimodal remote sensing data fusion: A comprehensive review
With the extremely rapid advances in remote sensing (RS) technology, a great quantity of
Earth observation (EO) data featuring considerable and complicated heterogeneity are …
Earth observation (EO) data featuring considerable and complicated heterogeneity are …
A review of methods for scaling remotely sensed data for spatial pattern analysis
Context Landscape ecologists have long realized the importance of scale when studying
spatial patterns and the need for a science of scaling. Remotely sensed data, a key …
spatial patterns and the need for a science of scaling. Remotely sensed data, a key …
A self-supervised remote sensing image fusion framework with dual-stage self-learning and spectral super-resolution injection
Pan-sharpening is a very productive technique to enhance the spatial details of multispectral
images with the aid of panchromatic images. Nowadays, deep learning-based pan …
images with the aid of panchromatic images. Nowadays, deep learning-based pan …
Pansharpening by convolutional neural networks in the full resolution framework
In recent years, there has been a growing interest in deep learning-based pansharpening.
Thus far, research has mainly focused on architectures. Nonetheless, model training is an …
Thus far, research has mainly focused on architectures. Nonetheless, model training is an …
Semantic segmentation of urban buildings using a high-resolution network (HRNet) with channel and spatial attention gates
S Seong, J Choi - Remote Sensing, 2021 - mdpi.com
In this study, building extraction in aerial images was performed using csAG-HRNet by
applying HRNet-v2 in combination with channel and spatial attention gates. HRNet-v2 …
applying HRNet-v2 in combination with channel and spatial attention gates. HRNet-v2 …
CADUI: Cross-attention-based depth unfolding iteration network for pansharpening remote sensing images
Z Li, J Li, F Zhang, L Fan - IEEE Transactions on Geoscience …, 2023 - ieeexplore.ieee.org
Pansharpening is an important technology for remote sensing imaging systems to obtain
high-resolution multispectral (HRMS) images. It mainly obtains HRMS images with uniform …
high-resolution multispectral (HRMS) images. It mainly obtains HRMS images with uniform …
Unsupervised deep learning-based pansharpening with jointly-enhanced spectral and spatial fidelity
In latest years, deep learning (DL) has gained a leading role in the pansharpening of
multiresolution images. Given the lack of ground truth data, most DL-based methods carry …
multiresolution images. Given the lack of ground truth data, most DL-based methods carry …
Band-wise hyperspectral image pansharpening using CNN model propagation
Hyperspectral (HS) pansharpening has received a growing interest in the last few years as
testified by a large number of research papers and challenges. It consists in a pixel-level …
testified by a large number of research papers and challenges. It consists in a pixel-level …
Fast full-resolution target-adaptive cnn-based pansharpening framework
In the last few years, there has been a renewed interest in data fusion techniques, and, in
particular, in pansharpening due to a paradigm shift from model-based to data-driven …
particular, in pansharpening due to a paradigm shift from model-based to data-driven …
Sscaconv: Self-guided spatial-channel adaptive convolution for image fusion
Pansharpening, which attempts to obtain a high-resolution multispectral (HR-MS) image by
fusing a panchromatic (PAN) image with a low-resolution multispectral (LR-MS) image, is a …
fusing a panchromatic (PAN) image with a low-resolution multispectral (LR-MS) image, is a …