TnTViT-G: Transformer in Transformer Network for Guidance Super Resolution
IEEE Access, 2023 Image Super Resolution is a potential approach that can improve the image quality of low-resolution optical sensors, leading to improved performance in various industrial applications.
Armin Mehri +2 more
doaj +1 more source
MSISR-STF: Spatiotemporal Fusion via Multilevel Single-Image Super-Resolution
, 2023 Due to technological limitations and budget constraints, spatiotemporal image fusion uses the complementarity of high temporal–low spatial resolution (HTLS) and high spatial–low temporal resolution (HSLT) data to obtain high temporal and ...
Junqing Fan +5 more
core +1 more source
Single-image super-resolution improvement of X-ray single-particle diffraction images using convolutional neural network [PDF]
, 2021 Femtosecond X-ray pulse lasers are promising probes for elucidating the multi-conformational states of biomolecules because they enable snapshots of single biomolecules to be observed as coherent diffraction images.
Yoshinobu, Akinaga +3 more
core +2 more sources
Deep Back-ProjectiNetworks for Single Image Super-Resolution [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 Previous feed-forward architectures of recently proposed deep super-resolution networks learn the features of low-resolution inputs and the non-linear mapping from those to a high-resolution output. However, this approach does not fully address the mutual dependencies of low- and high-resolution images.
Muhammad Haris 0002 +2 more
openaire +3 more sources
Super-Resolution Microscopy: A Virus’ Eye View of the Cell [PDF]
, 2014 It is difficult to observe the molecular choreography between viruses and host cell components, as they exist on a spatial scale beyond the reach of conventional microscopy.
Grove, J, Grove, Joe, Joe Grove
core +1 more source
Single-shot super-resolution quantitative phase imaging allowed by coherence gate shaping
, 2023 Biomedical and metasurface researchers repeatedly reach for quantitative phase imaging (QPI) as their primary imaging technique due to its high-throughput, label-free, quantitative nature. So far, very little progress has been made toward achieving super-
Petr Bouchal +5 more
core +1 more source
Multi-Image Super Resolution of Remotely Sensed Images Using Residual Attention Deep Neural Networks
Remote Sensing, 2020 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 to extract further information and knowledge from captured data ...
Francesco Salvetti +3 more
doaj +1 more source
4× Super‐resolution of unsupervised CT images based on GAN
IET Image Processing, 2023 Improving the resolution of computed tomography (CT) medical images can help doctors more accurately identify lesions, which is important in clinical diagnosis.
Yunhe Li +3 more
doaj +1 more source
Super-resolution reconstruction of brain magnetic resonance images via lightweight autoencoder
Informatics in Medicine Unlocked, 2021 Magnetic Resonance Imaging (MRI) is useful to provide detailed anatomical information such as images of tissues and organs within the body that are vital for quantitative image analysis. However, typically the MR images acquired lacks adequate resolution
J. Andrew +6 more
doaj +1 more source
Local semi-supervised regression for single-image super-resolution
, 2011 In this paper, we propose a local semi-supervised learning-based algorithm for single-image super-resolution. Different from most of example-based algorithms, the information of test patches is considered during learning local regression functions which ...
Xiaoli Pan +17 more
core +1 more source