[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 …
Using artificial intelligence and data fusion for environmental monitoring: A review and future perspectives
Analyzing satellite images and remote sensing (RS) data using artificial intelligence (AI)
tools and data fusion strategies has recently opened new perspectives for environmental …
tools and data fusion strategies has recently opened new perspectives for environmental …
Multispectral and hyperspectral image fusion in remote sensing: A survey
G Vivone - Information Fusion, 2023 - Elsevier
The fusion of multispectral (MS) and hyperspectral (HS) images has recently been put in the
spotlight. The combination of high spatial resolution MS images with HS data showing a …
spotlight. The combination of high spatial resolution MS images with HS data showing a …
Enhanced autoencoders with attention-embedded degradation learning for unsupervised hyperspectral image super-resolution
Recently, unmixing-based networks have shown significant potential in unsupervised
multispectral-aided hyperspectral image super-resolution (MS-aided HS-SR) task …
multispectral-aided hyperspectral image super-resolution (MS-aided HS-SR) task …
[HTML][HTML] Deep learning in remote sensing applications: A meta-analysis and review
Deep learning (DL) algorithms have seen a massive rise in popularity for remote-sensing
image analysis over the past few years. In this study, the major DL concepts pertinent to …
image analysis over the past few years. In this study, the major DL concepts pertinent to …
Mapping of cropland, cropping patterns and crop types by combining optical remote sensing images with decision tree classifier and random forest
Mapping and monitoring the distribution of croplands and crop types support policymakers
and international organizations by reducing the risks to food security, notably from climate …
and international organizations by reducing the risks to food security, notably from climate …
Zero-shot hyperspectral sharpening
Fusing hyperspectral images (HSIs) with multispectral images (MSIs) of higher spatial
resolution has become an effective way to sharpen HSIs. Recently, deep convolutional …
resolution has become an effective way to sharpen HSIs. Recently, deep convolutional …
Hyperspectral image super-resolution via deep spatiospectral attention convolutional neural networks
Hyperspectral images (HSIs) are of crucial importance in order to better understand features
from a large number of spectral channels. Restricted by its inner imaging mechanism, the …
from a large number of spectral channels. Restricted by its inner imaging mechanism, the …
Regularizing hyperspectral and multispectral image fusion by CNN denoiser
Hyperspectral image (HSI) and multispectral image (MSI) fusion, which fuses a low-spatial-
resolution HSI (LR-HSI) with a higher resolution multispectral image (MSI), has become a …
resolution HSI (LR-HSI) with a higher resolution multispectral image (MSI), has become a …
Spatial-spectral structured sparse low-rank representation for hyperspectral image super-resolution
Hyperspectral image super-resolution by fusing high-resolution multispectral image (HR-
MSI) and low-resolution hyperspectral image (LR-HSI) aims at reconstructing high resolution …
MSI) and low-resolution hyperspectral image (LR-HSI) aims at reconstructing high resolution …