Results 11 to 20 of about 209,737 (306)
A Review of GAN-Based Super-Resolution Reconstruction for Optical Remote Sensing Images
Remote Sensing, 2023 High-resolution images have a wide range of applications in image compression, remote sensing, medical imaging, public safety, and other fields. The primary objective of super-resolution reconstruction of images is to reconstruct a given low-resolution ...
Xuan Wang +3 more
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Super-resolution wavefront reconstruction
Astronomy & Astrophysics, 2022 Context.Cutting-edge, ground-based astronomical instruments are fed by adaptive optics (AO) systems that are aimed at providing high performance down to the visible wavelength domain on 10 m class telescopes and in the near infrared for the first generation instruments of Extremely Large Telescopes (ELTs).
Sylvain Oberti +4 more
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A DEM Super-Resolution Reconstruction Network Combining Internal and External Learning
Remote Sensing, 2022 The study of digital elevation model (DEM) super-resolution reconstruction algorithms has solved the problem of the need for high-resolution DEMs. However, the DEM super-resolution reconstruction algorithm itself is an inverse problem, and making full ...
Xu Lin +6 more
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Super-resolution reconstruction based on two-stage residual neural network
Machine Learning with Applications, 2021 With the constant update of deep learning technology, the super-resolution reconstruction technology based on deep learning has also attained a significant breakthrough. This paper primarily discusses the integration of deep learning and super-resolution
Lin Dong, Kohei Inoue
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Joint Image Reconstruction and Super-Resolution for Accelerated Magnetic Resonance Imaging
Bioengineering, 2023 Magnetic resonance (MR) image reconstruction and super-resolution are two prominent techniques to restore high-quality images from undersampled or low-resolution k-space data to accelerate MR imaging. Combining undersampled and low-resolution acquisition
Wei Xu +6 more
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Iterative Back Projection Network Based on Deformable 3D Convolution
IEEE Access, 2023 Video super-resolution technology enhances the display quality of videos by obtaining high-resolution videos from low-resolution videos. Unlike single-image super-resolution, utilizing information between adjacent video frames is crucial in video super ...
Chengzhi Luo, Bing Li, Feng Liu
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Guided filter-based multi-scale super-resolution reconstruction
CAAI Transactions on Intelligence Technology, 2020 The learning-based super-resolution reconstruction method inputs a low-resolution image into a network, and learns a non-linear mapping relationship between low-resolution and high-resolution through the network.
Xiaomei Feng +3 more
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3D MRI Reconstruction Based on 2D Generative Adversarial Network Super-Resolution
Sensors, 2021 The diagnosis of brain pathologies usually involves imaging to analyze the condition of the brain. Magnetic resonance imaging (MRI) technology is widely used in brain disorder diagnosis.
Hongtao Zhang +2 more
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Super-Resolution Reconstruction of Arbitrary Scale Images Based on Multi-Resolution Feature Fusion [PDF]
Jisuanji gongcheng, 2023 Traditional deep learning image super-resolution reconstruction network only extracts features at a fixed resolution and cannot integrate advanced semantic information.
Wenzhuo FAN, Tao WU, Junping XU, Qingqing LI, Jianlin ZHANG, Meihui LI, Yuxing WEI
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MRI inter-slice reconstruction using super-resolution [PDF]
Magnetic Resonance Imaging, 2001 MRI reconstruction using super-resolution is presented and shown to improve spatial resolution in cases when spatially-selective RF pulses are used for localization. In 2-D multislice MRI, the resolution in the slice direction is often lower than the in-plane resolution. For certain diagnostic imaging applications, isotropic resolution is necessary but
H, Greenspan +3 more
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