Results 11 to 20 of about 255,777 (278)
Hybrid spectral CT reconstruction. [PDF]
PLoS ONE, 2017 Current photon counting x-ray detector (PCD) technology faces limitations associated with spectral fidelity and photon starvation. One strategy for addressing these limitations is to supplement PCD data with high-resolution, low-noise data acquired with ...
Darin P Clark, Cristian T Badea
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Accelerating ptychographic reconstructions using spectral initializations [PDF]
Optics Letters, 2021 Ptychography is a promising phase retrieval technique for label-free quantitative phase imaging. Recent advances in phase retrieval algorithms witnessed the development of spectral methods to accelerate gradient descent algorithms. Using spectral initializations on experimental data, for the first time, we report three times faster ptychographic ...
Valzania, Lorenzo +2 more
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Deep‐learning based on‐chip rapid spectral imaging with high spatial resolution
Chip, 2023 : Spectral imaging extends the concept of traditional color cameras to capture images across multiple spectral channels and has broad application prospects.
Jiawei Yang +5 more
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Spectral reconstruction with deep neural networks [PDF]
Physical Review D, 2020 We explore artificial neural networks as a tool for the reconstruction of spectral functions from imaginary time Green's functions, a classic ill-conditioned inverse problem. Our ansatz is based on a supervised learning framework in which prior knowledge is encoded in the training data and the inverse transformation manifold is explicitly parametrised ...
Lukas Kades +7 more
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Spectral Clustering for Jet Reconstruction
Proceedings of 41st International Conference on High Energy physics — PoS(ICHEP2022), 2022 We present a new approach to jet definition alternative to clustering methods, such as the anti-$k_T$ scheme, that exploit kinematic data directly. Instead the new method uses kinematic information to represent the particles in a multidimensional space, as in spectral clustering. After confirming its Infra-Red (IR) safety, we compare its performance in
Cerro, G. +6 more
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Spectral density reconstruction with Chebyshev polynomials
Physical Review E, 2022 14 pages, 6 ...
Joanna E. Sobczyk, Alessandro Roggero
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SpectralMAE: Spectral Masked Autoencoder for Hyperspectral Remote Sensing Image Reconstruction
Sensors, 2023 Accurate hyperspectral remote sensing information is essential for feature identification and detection. Nevertheless, the hyperspectral imaging mechanism poses challenges in balancing the trade-off between spatial and spectral resolution.
Lingxuan Zhu +4 more
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Spectral CT Reconstruction With Image Sparsity and Spectral Mean [PDF]
IEEE Transactions on Computational Imaging, 2016 Photon-counting detectors can acquire x-ray intensity data in different energy bins. The signal to noise ratio of resultant raw data in each energy bin is generally low due to the narrow bin width and quantum noise. To address this problem, here we propose an image reconstruction approach for spectral CT to simultaneously reconstructs x-ray attenuation
Yi, Zhang +5 more
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Spatial-spectral cube matching frame for spectral CT reconstruction [PDF]
Inverse Problems, 2018 Spectral computed tomography (CT) reconstructs the same scanned object from projections of multiple narrow energy windows, and it can be used for material identification and decomposition. However, the multi-energy projection dataset has a lower signal-noise-ratio (SNR), resulting in poor reconstructed image quality.
Weiwen Wu +5 more
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Reconstructing QCD spectral functions with Gaussian processes [PDF]
Physical Review D, 2022 We reconstruct ghost and gluon spectral functions in 2+1 flavor QCD with Gaussian process regression. This framework allows us to largely suppress spurious oscillations and other common reconstruction artifacts by specifying generic magnitude and length scale parameters in the kernel function.
Jan Horak +6 more
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