Results 31 to 40 of about 360,556 (315)
Super-resolution reconstruction of rock CT images based on Real-ESRGAN
Gong-kuang zidonghua, 2023 Due to factors such as image acquisition equipment and geological environment, rock CT images have low resolution and unclear details. However, existing image super-resolution reconstruction methods are prone to losing details when characterizing high ...
LI Gang +6 more
doaj +1 more source
Super-resolution Reconstruction of Remote Sensing Images Based on Joint Nonnegative Dictionary Learning [PDF]
Jisuanji gongcheng, 2016 Aiming at the super-resolution reconstruction of images,a super-resolution reconstruction algorithm for a single image based on joint nonnegative dictionary learning is proposed in this paper,and it is applied in the super-resolution reconstruction of ...
WEI Wei,WU Kongping,GUO Laigong,QIN Meng
doaj +1 more source
Super-resolution reconstruction for tongue MR images [PDF]
SPIE Proceedings, 2012 Magnetic resonance (MR) images of the tongue have been used in both clinical medicine and scientific research to reveal tongue structure and motion. In order to see different features of the tongue and its relation to the vocal tract it is beneficial to acquire three orthogonal image stacks-e.g., axial, sagittal and coronal volumes.
Jonghye Woo +5 more
openaire +2 more sources
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network [PDF]
Computer Vision and Pattern Recognition, 2016 Despite the breakthroughs in accuracy and speed of single image super-resolution using faster and deeper convolutional neural networks, one central problem remains largely unsolved: how do we recover the finer texture details when we super-resolve at ...
C. Ledig +8 more
semanticscholar +1 more source
Deep learning method for super-resolution reconstruction of the spatio-temporal flow field
Advances in Aerodynamics, 2023 The high-resolution (HR) spatio-temporal flow field plays a decisive role in describing the details of the flow field. In the acquisition of the HR flow field, traditional direct numerical simulation (DNS) and other methods face a seriously high ...
K. Bao +3 more
semanticscholar +1 more source
International Journal of Digital Earth, 2023 Vegetation is crucial for wetland ecosystems. Human activities and climate changes are increasingly threatening wetland ecosystems. Combining satellite images and deep learning for classifying marsh vegetation communities has faced great challenges ...
B. Fu +7 more
semanticscholar +1 more source
FRESH – FRI-based single-image super-resolution algorithm [PDF]
, 2016 In this paper, we consider the problem of single image super-resolution and propose a novel algorithm that outperforms state-of-the-art methods without the need of learning patches pairs from external data sets.
Dragotti, P, Wei, X
core +1 more source
AIP Advances, 2020 A general super-resolution (SR) reconstruction strategy is proposed to address the super-resolution reconstruction of temperature fields from low-resolution coarse temperature field data using convolutional neural networks.
Chen Kong +3 more
doaj +1 more source
Super-Resolution Time of Arrival Estimation Using Random Resampling in Compressed Sensing [PDF]
, 2018 There is a strong demand for super-resolution time of arrival (TOA) estimation techniques for radar applications that can that can exceed the theoretical limits on range resolution set by frequency bandwidth.
Fang SHANG +3 more
core +2 more sources
Unsupervised deep learning for super-resolution reconstruction of turbulence [PDF]
Journal of Fluid Mechanics, 2020 Recent attempts to use deep learning for super-resolution reconstruction of turbulent flows have used supervised learning, which requires paired data for training.
Hyojin Kim +3 more
semanticscholar +1 more source