نتایج جستجو برای: random undersampling

تعداد نتایج: 284925  

2014
Enrique A. Lopez-Poveda

Hearing impairment is a serious disease with increasing prevalence. It is defined based on increased audiometric thresholds but increased thresholds are only partly responsible for the greater difficulty understanding speech in noisy environments experienced by some older listeners or by hearing-impaired listeners. Identifying the additional factors and mechanisms that impair intelligibility is...

Journal: :Vision Research 1999
Dennis M Levi Stanley A Klein Vineeta Sharma

The present paper addresses whether topographical jitter or undersampling might limit pattern perception in foveal, peripheral and strabismic amblyopic vision. In the first experiment, we measured contrast thresholds for detecting and identifying the orientation (up, down, left, right) of E-like patterns comprised of Gabor samples. We found that detection and identification thresholds were both...

2001
Gary Bernstein

The familiar tools of Fourier analysis and Fisher matrices are applied to derive the uncertainties on photometric, astrometric, and weak-lensing measurements of stars and galaxies in real astronomical images. Many effects or functions that are ignored in basic exposure-time calculators can be included in this framework: pixels of size comparable to the stellar image; undersampled and dithered e...

2008
R. Ahmad L. C. Potter P. Kuppusamy

Introduction: In this work, we propose an oscillating radial sampling of k-space which shows a significant improvement in the reconstruction quality over the traditional radial sampling based reconstruction. The incoherency in spatial aliasing artifacts is selected as a criterion for optimizing the k-space trajectory. Adding oscillations reduces the coherency in the k-space trajectory and hence...

2007
Cameron Browne

Harmonograms are visual designs based on harmonic analyses of strings of characters. Fourier descriptors are synthesized according to character positions and values, and then traditional methods are used to generate the resulting curves. Undersampling introduces visual artifacts that actually enhance the final designs. While their primary use is for the creation of artistic designs, harmonogram...

2008
M. Doneva J. Sénégas P. Börnert H. Eggers A. Mertins

Introduction: The estimation of MR parameters, such as the relaxation times T1, T2 and diffusion coefficients D, requires the acquisition of multiple images at different sequence parameters, which is often associated with long acquisition times. These data show a high temporal correlation, which can be described by a model facilitating accelerated image acquisition by data undersampling as show...

2009
D. Yoon J. Fessler J-F. Nielsen A. Gilbert

Introduction We propose a novel compressed sensing algorithm for Phase Contrast MRI(PC-MRI) to estimate blood flow velocities. Blood flow velocities provide clinically useful information such as pressure gradients and PC-MRI has become an established technique to measure them. In conventional PC-MRI, velocity information is computed by comparing the phases of the velocity-encoded image and the ...

Journal: :JIP (Jurnal Informatika Polinema) 2022

Seleksi mahasiswa baru penerima Kartu Indonesia Pintar Kuliah (KIP Kuliah) dilakukan oleh setiap institusi untuk memilih yang benar-benar memiliki potensi akademik baik dan keterbatasan ekonomi. Pada penelitian ini menggunakan regresi logistik biner sebagai model klasifikasi. Data hasil preprocessing dibagi menjadi data training testing. Beberapa dibandingkan kinerjanya, asli, normalisasi, unde...

2016
Emeline Lugand Jérôme Yerly Hélène Feliciano Jérôme Chaptinel Matthias Stuber Ruud B van Heeswijk

Background Several cardiac T2 mapping techniques with varying T2 preparation (T2Prep) times have been proposed for the quantification of cardiac edema [1-3]. Among these, radial T2 mapping, which is robust to motion artifacts, suffers from a low signal-to-noise ratio (SNR) caused by the undersampling of the k-space periphery and by its density compensation function (DCF) (Fig. 1a). However, sin...

Journal: :Soft Comput. 2011
Julián Luengo Alberto Fernández Salvador García Francisco Herrera

In the classification framework there are problems in which the number of examples per class is not equitably distributed, formerly known as imbalanced data sets. This situation is a handicap when trying to identify the minority classes, as the learning algorithms are not usually adapted to such characteristics. An usual approach to deal with the problem of imbalanced data sets is the use of a ...

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