Results 31 to 40 of about 1,596,426 (191)
Image reconstruction from photon sparse data [PDF]
Scientific Reports, 2017 AbstractWe report an algorithm for reconstructing images when the average number of photons recorded per pixel is of order unity, i.e. photon-sparse data. The image optimisation algorithm minimises a cost function incorporating both a Poissonian log-likelihood term based on the deviation of the reconstructed image from the measured data and a ...
Mertens, Lena +4 more
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Development of the Senseiver for efficient field reconstruction from sparse observations
Nature Machine Intelligence, 2023 The reconstruction of complex time-evolving fields from sensor observations is a grand challenge. Frequently, sensors have extremely sparse coverage and low-resource computing capacity for measuring highly nonlinear phenomena. While numerical simulations
Javier E. Santos +5 more
semanticscholar +1 more source
Kernel Reconstruction ICA for Sparse Representation [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2015 Independent component analysis with soft reconstruction cost (RICA) has been recently proposed to linearly learn sparse representation with an overcomplete basis, and this technique exhibits promising performance even on unwhitened data. However, linear RICA may not be effective for the majority of real-world data because nonlinearly separable data ...
Yanhui, Xiao +4 more
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Joint-2D-SL0 Algorithm for Joint Sparse Matrix Reconstruction
International Journal of Antennas and Propagation, 2017 Sparse matrix reconstruction has a wide application such as DOA estimation and STAP. However, its performance is usually restricted by the grid mismatch problem. In this paper, we revise the sparse matrix reconstruction model and propose the joint sparse
Dong Zhang, Yongshun Zhang, Cunqian Feng
doaj +1 more source
Temperature Field Reconstruction Method for Acoustic Tomography Based on Multi-Dictionary Learning
Sensors, 2022 A reconstruction algorithm is proposed, based on multi-dictionary learning (MDL), to improve the reconstruction quality of acoustic tomography for complex temperature fields.
Yuankun Wei, Hua Yan, Yinggang Zhou
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Sparse ACEKF for phase reconstruction
Optics Express, 2013 We propose a novel low-complexity recursive filter to efficiently recover quantitative phase from a series of noisy intensity images taken through focus. We first transform the wave propagation equation and nonlinear observation model (intensity measurement) into a complex augmented state space model.
Jingshan, Zhong +3 more
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Sparse reconstruction of correlated multichannel activity [PDF]
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013 Parametric methods for modeling sinusoidal signals with line spectra have been studied for decades. In general, these methods start by representing each sinusoidal component by means of two complex exponential functions, thereby doubling the number of unknown parameters.
Peelman, S. +5 more
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Exact CS Reconstruction Condition of Undersampled Spectrum-Sparse Signals
Journal of Applied Mathematics, 2013 Compressive sensing (CS) reconstruction of a spectrum-sparse signal from undersampled data is, in fact, an ill-posed problem. In this paper, we mathematically prove that, in certain cases, the exact CS reconstruction of a spectrum-sparse signal from ...
Ying Luo +3 more
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Extreme Learning Machines as Encoders for Sparse Reconstruction
Fluids, 2018 Reconstruction of fine-scale information from sparse data is often needed in practical fluid dynamics where the sensors are typically sparse and yet, one may need to learn the underlying flow structures or inform predictions through assimilation into ...
S M Abdullah Al Mamun +2 more
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Physics informed neural fields for smoke reconstruction with sparse data [PDF]
ACM Transactions on Graphics, 2022 High-fidelity reconstruction of dynamic fluids from sparse multiview RGB videos remains a formidable challenge, due to the complexity of the underlying physics as well as the severe occlusion and complex lighting in the captured data.
Mengyu Chu +6 more
semanticscholar +1 more source