Results 61 to 70 of about 8,062,965 (379)
Deep Magnetic Resonance Image Reconstruction: Inverse Problems Meet Neural Networks
IEEE Signal Processing Magazine, 2020 Image reconstruction from undersampled k-space data has been playing an important role in fast magnetic resonance imaging (MRI). Recently, deep learning has demonstrated tremendous success in various fields and also shown potential in significantly ...
D. Liang, Jing Cheng, Ziwen Ke, L. Ying
semanticscholar +1 more source
3D point cloud generation reconstruction from single image based on image retrieval
Results in Optics, 2021 Most of the 3D point cloud generation methods from a single image are only applicable to a single target. However, the real image often contains multiple targets, which is difficult to generate 3D point clouds from the network directly.
Hui Chen, Yipeng Zuo, Yong Tong, Li Zhu
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Image Reconstruction in Optical Interferometry
, 2009 This tutorial paper describes the problem of image reconstruction from interferometric data with a particular focus on the specific problems encountered at optical (visible/IR) wavelengths.
Giovannelli, Jean-François +1 more
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Artificial Intelligence for MR Image Reconstruction: An Overview for Clinicians
Journal of Magnetic Resonance Imaging, 2020 Artificial intelligence (AI) shows tremendous promise in the field of medical imaging, with recent breakthroughs applying deep‐learning models for data acquisition, classification problems, segmentation, image synthesis, and image reconstruction. With an
Dana J. Lin +3 more
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HDR-GAN: HDR Image Reconstruction From Multi-Exposed LDR Images With Large Motions [PDF]
IEEE Transactions on Image Processing, 2020 Synthesizing high dynamic range (HDR) images from multiple low-dynamic range (LDR) exposures in dynamic scenes is challenging. There are two major problems caused by the large motions of foreground objects.
Yuzhen Niu +4 more
semanticscholar +1 more source
EURASIP Journal on Image and Video Processing, 2018 Considering the non-uniqueness and instability of concrete defect detection in construction engineering, ultrasonic time of flight data and maximum likelihood expectation maximization algorithm were proposed to improve the readability of the ultrasonic ...
Honghui Fan, Hongjin Zhu
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Reconstructing Vectorised Photographic Images [PDF]
2009 Conference for Visual Media Production, 2009 We address the problem of representing captured images in the continuous mathematical space more usually associated with certain forms of drawn ('vector') images. Such an image is resolution-independent so can be used as a master for varying resolution-specific formats.
Patterson, J.W. +2 more
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A Monte Carlo Template based analysis for Air-Cherenkov Arrays [PDF]
, 2014 We present a high-performance event reconstruction algorithm: an Image Pixel-wise fit for Atmospheric Cherenkov Telescopes (ImPACT). The reconstruction algorithm is based around the likelihood fitting of camera pixel amplitudes to an expected image ...
Hinton, J. A., Parsons, R. D.
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Image reconstruction by linear programming [PDF]
IEEE Transactions on Image Processing, 2005 One way of image denoising is to project a noisy image to the subspace of admissible images derived, for instance, by PCA. However, a major drawback of this method is that all pixels are updated by the projection, even when only a few pixels are corrupted by noise or occlusion.
Tsuda, K., Rätsch, G.
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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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