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   Articles with "sparse sampling" as a keyword



Fast shading correction for cone beam CT in radiation therapy via sparse sampling on planning CT

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recommendations! Published in 2017 at "Medical Physics"

DOI: 10.1002/mp.12190

Abstract: Purpose The image quality of cone beam computed tomography (CBCT) is limited by severe shading artifacts, hindering its quantitative applications in radiation therapy. In this work, we propose an image‐domain shading correction method using planning… read more here.

Keywords: sparse sampling; radiation therapy; shading correction; correction ... See more keywords

Exponential-Reproducing-Kernel-Based Sparse Sampling Method for Finite Rate of Innovation Signal with Arbitrary Pulse Echo Position

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recommendations! Published in 2019 at "Circuits, Systems, and Signal Processing"

DOI: 10.1007/s00034-018-0903-8

Abstract: AbstractAn exponential reproducing kernel (ERK) has been applied to data sparse sampling for finite rate of innovation (FRI) signals with the characteristic of flexible parameter setting in contrast to other sampling kernels. However, the signal… read more here.

Keywords: sparse sampling; pulse echo; reproducing kernel; exponential reproducing ... See more keywords

Novel Circuit Implementation Method for Pulse Signal Finite Rate of Innovation Sparse Sampling Based on an Improved Exponential Reproducing Kernel

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recommendations! Published in 2019 at "Circuits, Systems, and Signal Processing"

DOI: 10.1007/s00034-019-01076-3

Abstract: Finite rate of innovation sampling is a new signal sparse sampling method based on signal information freedom, which can considerably reduce the amount of sampling data. However, the researches on hardware circuit direct implementation of… read more here.

Keywords: implementation method; rate; sparse sampling; circuit ... See more keywords

Low-dose MDCT: evaluation of the impact of systematic tube current reduction and sparse sampling on the detection of degenerative spine diseases

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recommendations! Published in 2020 at "European Radiology"

DOI: 10.1007/s00330-020-07278-7

Abstract: Objectives To investigate potential radiation dose reduction for multi-detector computed tomography (MDCT) exams of the spine by using sparse sampling and virtually lowered tube currents combined with statistical iterative reconstruction (SIR). Methods MDCT data of… read more here.

Keywords: sparse sampling; degenerative changes; tube; dose ... See more keywords

The neural correlates of referential communication: Taking advantage of sparse-sampling fMRI to study verbal communication with a real interaction partner

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recommendations! Published in 2021 at "Brain and Cognition"

DOI: 10.1016/j.bandc.2021.105801

Abstract: This paper introduces an innovative functional magnetic resonance imaging (fMRI) protocol to study real verbal interactions while limiting the impact of speech-related movement artefacts. This protocol is based on a sparse sampling acquisition technique and… read more here.

Keywords: sparse sampling; communication; interaction partner; study ... See more keywords

Sound field reconstruction with sparse sampling and the equivalent source method

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recommendations! Published in 2018 at "Mechanical Systems and Signal Processing"

DOI: 10.1016/j.ymssp.2018.02.031

Abstract: Abstract The equivalent source method is reformulated under the compressive sensing framework for tackling with the spatially extended sound source. The sound field to be reconstructed is first modeled using the equivalent source method according… read more here.

Keywords: source method; sparse sampling; source; sound field ... See more keywords

High-efficiency sound source localization using data-driven sparse sampling with validation using monopole laser sound source

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recommendations! Published in 2024 at "AIP Advances"

DOI: 10.1063/5.0205567

Abstract: This study proposes a framework that reduces the calculation cost of sound source localization with the Amiet model, using a data-driven sparse sampling method. This method accelerates the calculation of the steering vector used in… read more here.

Keywords: sparse sampling; source; data driven; driven sparse ... See more keywords

A Subspace Approach to Sparse-Sampling-Based Multi-Attribute Data Aggregation in IoT

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recommendations! Published in 2022 at "IEEE Internet of Things Journal"

DOI: 10.1109/jiot.2022.3161720

Abstract: The emergence of the heterogeneous Internet of Things (IoT) has realized the demand for multi-attribute data collection in response to the increasing demand for information in diverse applications. Sparse sampling has been used to reduce… read more here.

Keywords: sparse sampling; real time; attribute data; multi attribute ... See more keywords

Sparse Sampling in Fractional Fourier Domain: Recovery Guarantees and Cramér–Rao Bounds

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recommendations! Published in 2024 at "IEEE Signal Processing Letters"

DOI: 10.1109/lsp.2024.3398372

Abstract: Sampling theory in fractional Fourier Transform (FrFT) domain has been studied extensively in the last decades. This interest stems from the ability of the FrFT to generalize the traditional Fourier Transform, broadening the traditional concept… read more here.

Keywords: sparse sampling; cram rao; recovery; fractional fourier ... See more keywords

Efficient Array Pattern Synthesis via Principal Angle-Based Sparse Sampling (PABSS)

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recommendations! Published in 2025 at "IEEE Transactions on Antennas and Propagation"

DOI: 10.1109/tap.2025.3539963

Abstract: This article presents the principal angle-based sparse sampling (PABSS) method, developed to enhance the efficiency of array pattern synthesis by streamlining the angular samples. Through the analysis of the correlation between array manifold components using… read more here.

Keywords: angle based; sparse sampling; synthesis; array ... See more keywords

Alpha Matting With KL-Divergence-Based Sparse Sampling

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recommendations! Published in 2017 at "IEEE Transactions on Image Processing"

DOI: 10.1109/tip.2017.2718664

Abstract: In this paper, we present a new sampling-based alpha matting approach for the accurate estimation of foreground and background layers of an image. Previous sampling-based methods typically rely on certain heuristics in collecting representative samples… read more here.

Keywords: divergence based; sparse sampling; matting divergence; divergence ... See more keywords