Results 31 to 40 of about 3,652,577 (286)
Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution [PDF]
Computer Vision and Pattern Recognition, 2017 Convolutional neural networks have recently demonstrated high-quality reconstruction for single-image super-resolution. In this paper, we propose the Laplacian Pyramid Super-Resolution Network (LapSRN) to progressively reconstruct the sub-band residuals ...
Wei-Sheng Lai +3 more
semanticscholar +1 more source
Regulation of ER-Golgi Transport Dynamics by GTPases in Budding Yeast
Frontiers in Cell and Developmental Biology, 2018 A large number of proteins are synthesized de novo in the endoplasmic reticulum (ER). They are transported through the Golgi apparatus and then delivered to their proper destinations.
Yasuyuki Suda +4 more
doaj +1 more source
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.
Xiaojie Chu, Liangyu Chen, Wenqing Yu
semanticscholar +1 more source
JISA (Jurnal Informatika dan Sains), 2021 This problem addresses the problem of low-resolution image (noisy) that will proof later by PSNR number. The best way to improve this low-resolution problem is by utilizing Super Resolution (SR) algorithm methodology.
Muhamad Ghofur, Tjong Wan Sen
doaj +1 more source
Improving spatial resolution of confocal Raman microscopy by super-resolution image restoration [PDF]
, 2016 A new super-resolution image restoration confocal Raman microscopy method (SRIR-RAMAN) is proposed for improving the spatial resolution of confocal Raman microscopy. This method can recover the lost high spatial frequency of the confocal Raman microscopy
Cui, Han +5 more
core +1 more source
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
semanticscholar +1 more source
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
doaj +1 more source
124-Color Super-resolution Imaging by Engineering DNA-PAINT Blinking Kinetics [PDF]
, 2019 Optical super-resolution techniques reach unprecedented spatial resolution down to a few nanometers. However, efficient multiplexing strategies for the simultaneous detection of hundreds of molecular species are still elusive.
Ganji, M. +13 more
core +3 more sources
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
doaj +1 more source
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
doaj +1 more source