Real-world single image super-resolution: A brief review
Single image super-resolution (SISR), which aims to reconstruct a high-resolution (HR)
image from a low-resolution (LR) observation, has been an active research topic in the area …
image from a low-resolution (LR) observation, has been an active research topic in the area …
[HTML][HTML] UAV & satellite synergies for optical remote sensing applications: A literature review
E Alvarez-Vanhard, T Corpetti, T Houet - Science of remote sensing, 2021 - Elsevier
Unmanned aerial vehicles (UAVs) and satellite constellations are both essential Earth
Observation (EO) systems for monitoring land surface dynamics. The former is frequently …
Observation (EO) systems for monitoring land surface dynamics. The former is frequently …
[HTML][HTML] An overview of deep learning in medical imaging focusing on MRI
AS Lundervold, A Lundervold - Zeitschrift für Medizinische Physik, 2019 - Elsevier
What has happened in machine learning lately, and what does it mean for the future of
medical image analysis? Machine learning has witnessed a tremendous amount of attention …
medical image analysis? Machine learning has witnessed a tremendous amount of attention …
Satellite video super-resolution via multiscale deformable convolution alignment and temporal grouping projection
As a new earth observation tool, satellite video has been widely used in remote-sensing
field for dynamic analysis. Video super-resolution (VSR) technique has thus attracted …
field for dynamic analysis. Video super-resolution (VSR) technique has thus attracted …
[HTML][HTML] Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks
Despite the state-of-the-art performance for medical image segmentation, deep
convolutional neural networks (CNNs) have rarely provided uncertainty estimations …
convolutional neural networks (CNNs) have rarely provided uncertainty estimations …
Deep learning in bioinformatics: Introduction, application, and perspective in the big data era
Deep learning, which is especially formidable in handling big data, has achieved great
success in various fields, including bioinformatics. With the advances of the big data era in …
success in various fields, including bioinformatics. With the advances of the big data era in …
MICU: Image super-resolution via multi-level information compensation and U-net
Y Chen, R Xia, K Yang, K Zou - Expert Systems with Applications, 2024 - Elsevier
Abstract Recently, Deep Convolutional Neural Networks have demonstrated high-quality
reconstruction in image super-resolution procedure. In this paper, we propose improved …
reconstruction in image super-resolution procedure. In this paper, we propose improved …
Super-resolution for remote sensing images via local–global combined network
Super-resolution is an image processing technology that recovers a high-resolution image
from a single or sequential low-resolution images. Recently deep convolutional neural …
from a single or sequential low-resolution images. Recently deep convolutional neural …
An integrated framework for the spatio–temporal–spectral fusion of remote sensing images
Remote sensing satellite sensors feature a tradeoff between the spatial, temporal, and
spectral resolutions. In this paper, we propose an integrated framework for the spatio …
spectral resolutions. In this paper, we propose an integrated framework for the spatio …
[HTML][HTML] Multi-image super resolution of remotely sensed images using residual attention deep neural networks
Convolutional Neural Networks (CNNs) consistently proved state-of-the-art results in image
Super-resolution (SR), representing an exceptional opportunity for the remote sensing field …
Super-resolution (SR), representing an exceptional opportunity for the remote sensing field …