Results 41 to 50 of about 3,010,100 (313)
Review and Prospect of Image Super-Resolution Technology
Jisuanji kexue yu tansuo, 2020 Image super-resolution (SR) is an important type of image processing technology for improving image and video resolution in computer vision. In recent years, thanks to the success of neural networks, image super-resolution technology based on deep ...
LIU Ying, ZHU Li, LIM Kengpang, LI Yinghua, WANG Fuping, LU Jin
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mapSR: A Deep Neural Network for Super-Resolution of Raster Map
ISPRS International Journal of Geo-Information, 2023 The purpose of multisource map super-resolution is to reconstruct high-resolution maps based on low-resolution maps, which is valuable for content-based map tasks such as map recognition and classification.
Honghao Li, Xiran Zhou, Zhigang Yan
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Generalized Face Super-Resolution [PDF]
IEEE Transactions on Image Processing, 2008 Existing learning-based face super-resolution (hallucination) techniques generate high-resolution images of a single facial modality (i.e., at a fixed expression, pose and illumination) given one or set of low-resolution face images as probe. Here, we present a generalized approach based on a hierarchical tensor (multilinear) space representation for ...
Jia, K, Gong, SG
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Energy Reports, 2022 Water is the source of life and a very important part of life. However, the current water resources security is facing global challenges. Affected by climate change and human factors, how to quickly realize the continuous monitoring of water resources ...
Lei Feng +5 more
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SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Models [PDF]
Neurocomputing, 2021 Single image super-resolution (SISR) aims to reconstruct high-resolution (HR) images from the given low-resolution (LR) ones, which is an ill-posed problem because one LR image corresponds to multiple HR images. Recently, learning-based SISR methods have
Haoying Li +6 more
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NAFSSR: Stereo Image Super-Resolution Using NAFNet [PDF]
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2022 Stereo image super-resolution aims at enhancing the quality of super-resolution results by utilizing the complementary information provided by binocular systems.
X. Chu, Liangyu Chen, Wenqing Yu
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MultiDimensional Sparse Super-Resolution [PDF]
SIAM Journal on Mathematical Analysis, 2019 The authors consider the computation of the positions and amplitudes of pointwise sources from linear measurements affected by additive noise. A regularized version of this problem is obtained by a minimization problem where the total variation of the solution is used as regularization term.
Poon, Clarice, Peyré, Gabriel
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Role of Atg8 in the regulation of vacuolar membrane invagination
Scientific Reports, 2019 Cellular heat stress can cause damage, and significant changes, to a variety of cellular structures. When exposed to chronically high temperatures, yeast cells invaginate vacuolar membranes.
Ayane Ishii +7 more
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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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Unsupervised Degradation Representation Learning for Blind Super-Resolution [PDF]
Computer Vision and Pattern Recognition, 2021 Most existing CNN-based super-resolution (SR) methods are developed based on an assumption that the degradation is fixed and known (e.g., bicubic downsampling).
Longguang Wang +6 more
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