Results 21 to 30 of about 360,556 (315)
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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Texture super-resolution for 3D reconstruction [PDF]
2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA), 2017 We describe a method for producing a high quality texture atlas for 3D models by fully exploiting the information contained in dense video sequences via super-resolution techniques. The intrinsic precision limitations of multi-view reconstruction techniques are analyzed and overcome.
Calum Burns +2 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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Guaranteed reconstruction for image super-resolution [PDF]
2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2013 This paper presents a new reconstruction operator to be used in a super-resolution scheme. Here, by reconstruction in super-resolution, we mean the back-projection operation, i.e. the way K low resolution (LR) images are aggregated to obtain a smooth high resolution (HR) image.
Graba, Farès +3 more
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Safety Helmet Detection Based on YOLOv5 Driven by Super-Resolution Reconstruction
Italian National Conference on Sensors, 2023 High-resolution image transmission is required in safety helmet detection problems in the construction industry, which makes it difficult for existing image detection methods to achieve high-speed detection.
Ju Han +4 more
semanticscholar +1 more source
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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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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Transformer and GAN Based Super-Resolution Reconstruction Network for Medical Images [PDF]
arXiv.org, 2022 —Because of the necessity to obtain high-quality im- ages with minimal radiation doses, such as in low-field magnetic resonance imaging, super-resolution reconstruction in medical imaging has become more popular (MRI).
Weizhi Du, Harvery Tian
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NeuroImage, 2021 Diffusion MRI (dMRI) can probe the tissue microstructure but suffers from low signal-to-noise ratio (SNR) whenever high resolution is combined with high diffusion encoding strengths.
Geraline Vis +3 more
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Super-resolution reconstruction of turbulent flows with machine learning [PDF]
Journal of Fluid Mechanics, 2018 We use machine learning to perform super-resolution analysis of grossly under-resolved turbulent flow field data to reconstruct the high-resolution flow field.
Kai Fukami, K. Fukagata, K. Taira
semanticscholar +1 more source