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Super-resolution of spatiotemporal event-stream image captured by the asynchronous temporal contrast vision sensor
[article]
2018
arXiv
pre-print
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Firstly, the event number of each pixel of the HR DVS image is determined with a sparse signal representation based method to obtain the HR event-count map from that of the LR DVS recording. ...
rate function. ...
resolution enhancement of the event-count map, 66 event-count maps of 66 DVS recordings
were used to train an over-complete dictionary for sparse representation. 3×3 LR patches with overlap
of 1 pixel ...
arXiv:1802.02398v2
fatcat:a4jee76d6zb6zk5hztfxdjl6qa
Sparse Regression Algorithm for Activity Estimation in $\gamma$ Spectrometry
2013
IEEE Transactions on Signal Processing
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We show in this paper that the problem of counting rate estimation can be interpreted as a sparse regression problem. ...
We consider the counting rate estimation of an unknown radioactive source, which emits photons at times modeled by an homogeneous Poisson process. ...
The proposed algorithm for counting rate estimation is then studied on a real dataset. ...
doi:10.1109/tsp.2013.2264811
fatcat:cf4pidjsh5hzlcpkrkbai6kha4
Waveform design and high-resolution imaging of cognitive radar based on compressive sensing
2012
Science China Information Sciences
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Then, we propose the spectrum-sparse waveform design criterion and the reconstruction algorithm for a highresolution range profile (HRRP) based on CS. ...
If the signal is sparse enough, it can be sampled at a rate much lower than the Nyquist rate and reconstructed with overwhelming probability by solving an inverse problem either through a linear program ...
The imaging algorithm for a spectrum-sparse OFDM-LFM signal is summarized in the flow charts shown in Figures 2 and 3 . ...
doi:10.1007/s11432-011-4527-x
fatcat:ldah4jsbtvamhpwwjjngx7jrue
Adaptive wavelet graph model for Bayesian tomographic reconstruction
2002
IEEE Transactions on Image Processing
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This results in a graph dependency structure which is more general than a quadtree, enabling the model to produce smooth estimates even for simple wavelet bases such as the Haar basis. ...
In conjunction with the wavelet graph model, we present a computationally efficient multiresolution image reconstruction algorithm. ...
Rouze for his valuable comments. ...
doi:10.1109/tip.2002.801586
pmid:18244672
fatcat:4p2qlqpq7rhkdph34vvo7ucbsi
2020 Index IEEE Transactions on Computational Imaging Vol. 6
2020
IEEE Transactions on Computational Imaging
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., +, TCI 2020 569-578 IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING, VOL. 6, 2020 + Check author entry for coauthors Nonhomogeneous media Efficient Regularized Field Map Estimation in 3D MRI. ...
Detectors An End-to-End Deep Network for Reconstructing CT Images Directly From Sparse Sinograms. ...
., +, TCI 2020 125-137 Truncation Correction for X-ray Phase-Contrast Region-of-Interest Tomography. Felsner, L., +, TCI 2020 625-639 ...
doi:10.1109/tci.2021.3054596
fatcat:puij7ztll5ai7alxrmqzsupcny
Ray prioritization using stylization and visual saliency
2012
Computers & graphics
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In addition, we present an efficient, adaptively aligned fractal pattern that is used to reconstruct the image from sparse sampling data. ...
Furthermore, this paper presents an algorithm which uses our method in order to guarantee a desired minimal frame rate. ...
) for providing their source code. ...
doi:10.1016/j.cag.2012.03.037
fatcat:esepvc6xlvhanmq6is32n3kile
Linear-Nonlinear-Poisson Neuron Networks Perform Bayesian Inference On Boltzmann Machines
[article]
2013
arXiv
pre-print
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We show that with neurally plausible settings, the whole network is capable of representing any Boltzmann machine and performing a semi-stochastic Bayesian inference algorithm lying between Gibbs sampling ...
Acknowledgement I want to thank Geoffrey Hinton, Mikhail Belkin, DeLiang Wang, Brian Kulis for helpful discussion and The Ohio Supercomputer Center for providing computation resource. ...
For example, properties of visual area V2 are found to be comparable to those on the sparse autoencoder networks [3] ; the sparse coding learning algorithm [4] is originated directly from neuroscience ...
arXiv:1210.8442v3
fatcat:k2pxrrurebg4ld7hgqiehzif24
Rate-distortion via Markov chain Monte Carlo
2008
2008 IEEE International Symposium on Information Theory
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of the reconstruction, and the point sought on the rate-distortion curve. ...
We show that the proposed algorithms achieve optimum rate-distortion performance in the limits of large number of iterations, and sequence length, when employed on any stationary ergodic source. ...
The reason is twofold: first, for larger alphabet sizes the contexts will be too sparse to give a true estimate of the empirical entropy of the reconstruction block, even for small values of k. ...
doi:10.1109/isit.2008.4595107
dblp:conf/isit/JalaliW08
fatcat:azfoieixrjbjffqahvwp5llm6u
A Pipeline for Classifying Relationships Using Dense SNP/SNV Data and Putative Pedigree Information
2015
Genetic Epidemiology
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Here, we present a set of approaches for classifying relationships in GWAS datasets or large-scale sequencing datasets. ...
Finally, we propose classification pipelines for checking and identifying relationships in datasets containing a large number of small pedigrees. ...
Marazita for providing the COHRA (US) and GENEVA (Guatemala) datasets. We also want to thank the reviewers for their valuable comments and suggestions. ...
doi:10.1002/gepi.21948
pmid:26709242
pmcid:PMC5146993
fatcat:jp6omxsvwvfkdmxzwwcs3pd7km
Sparsity-Based STAP Design Based on Alternating Direction Method with Gain/Phase Errors
[article]
2017
arXiv
pre-print
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using the reconstructed spatio-Doppler profiles. ...
Simulations are conducted to illustrate the benefits of the proposed algorithm. ...
problem as a sparse recovery/representation (SR) problem or a low-rank matrix estimation problem [84] . ...
arXiv:1706.07975v1
fatcat:kchef5yebbdqtoejb26hlnjdai
Recovery from Linear Measurements with Complexity-Matching Universal Signal Estimation
[article]
2014
arXiv
pre-print
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We incorporate some techniques to accelerate the algorithm while providing comparable and in many cases better reconstruction quality than existing algorithms. ...
We provide theoretical results that support the algorithmic feasibility of universal MAP estimation using a Markov chain Monte Carlo implementation, which is computationally challenging. ...
Existing CS algorithms fail at reconstructing this signal, because this source is not sparse.
FFig. 7 . 7 . ...
arXiv:1204.2611v3
fatcat:cchr3k2cebburjmu2atmkjfizu
Recovery From Linear Measurements With Complexity-Matching Universal Signal Estimation
2015
IEEE Transactions on Signal Processing
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We incorporate some techniques to accelerate the algorithm while providing comparable and in many cases better reconstruction quality than existing algorithms. ...
We provide theoretical results that support the algorithmic feasibility of universal MAP estimation using a Markov chain Monte Carlo implementation, which is computationally challenging. ...
Existing CS algorithms fail at reconstructing this signal, because this source is not sparse.
FFig. 7 . 7 . ...
doi:10.1109/tsp.2015.2393845
fatcat:hoxpxgztlrbipfaye4ca3ygqfi
Metabolic Pathway Inference from Time Series Data: A Non Iterative Approach
[chapter]
2011
Lecture Notes in Computer Science
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In this way we can avoid over-fitting, which is another often encountered problem in network reconstruction, and thus obtain better estimates for the parameters. ...
Our reconstruction method can incorporate an arbitrary a priori known network structure as well as positivity constraints on the reaction rates. ...
This work results from a collaboration between plant biologists, statisticians and mathematicians, initiated by the Netherlands Consortium for Systems Biology (NCSB) and Centre for Biosystems Genomics ...
doi:10.1007/978-3-642-24855-9_9
fatcat:mjrlsyyijzfvjhxtkwkydhmiuu
Experimental 3D Coherent Diffractive Imaging from photon-sparse random projections
[article]
2018
arXiv
pre-print
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The analog experiment provides an invaluable cross-check on the fidelity of the reconstructed data that is not available during XFEL experiments. ...
The routine atomic-resolution structure determination of single particles is expected to have profound implications for probing the structure-function relationship in systems ranging from energy materials ...
Therefore, we regard their contribution to the total count rate as negligible in this area [57]. ...
arXiv:1811.05883v1
fatcat:dg2ikfcu6jgwdjavvjpcmudksi
The Impact of Using Related Individuals for Haplotype Reconstruction in Population Studies
2005
Genetics
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Recent studies have highlighted the dangers of using haplotypes reconstructed directly from population data for a fine-scale mapping analysis. ...
To reconstruct haplotypes, we introduce an EM-based algorithm that can efficiently accommodate unrelated individuals, parent-child trios, and arbitrarily large half-sib pedigrees. ...
Michael Schouten also thanks Michalis Titsias for his technical insight and Alan Stubbs and Vivian Fu for their comments on the manuscript. ...
doi:10.1534/genetics.105.042762
pmid:15944347
pmcid:PMC1456835
fatcat:pfzzhjorhzdstawyfil6mrhtcq
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