Y
Yoad Yagil
Researcher at Philips
Publications - 50
Citations - 1527
Yoad Yagil is an academic researcher from Philips. The author has contributed to research in topics: Percolation threshold & Imaging phantom. The author has an hindex of 16, co-authored 44 publications receiving 1235 citations. Previous affiliations of Yoad Yagil include Tel Aviv University & University of Cambridge.
Papers
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Journal ArticleDOI
Transmittance and reflectance in situ measurements of semicontinuous gold films during deposition
TL;DR: In this article, the authors measured in situ reflectance and transmittance of percolating gold films over the entire range of surface coverage P, in the IR regime (1.7 and 2.2 μm).
Proceedings ArticleDOI
A systematic approach to SER estimation and solutions
H.T. Nguyen,Yoad Yagil +1 more
TL;DR: In this paper, a method for estimating Soft Error Rate (SER) and a systematic approach to identifying SER solutions is described, which is the first step in identifying if a problem exists and what measures are necessary to solve the problem.
Journal ArticleDOI
Chip-level soft error estimation method
TL;DR: In this paper, a review of considerations necessary for the prediction of soft error rates (SERs) for microprocessor designs is given, and the impact of logical and architectural filtering on SER calculations is discussed.
Journal ArticleDOI
Optical properties of thin semicontinuous gold films over a wavelength range of 2.5 to 500 μm
TL;DR: It is shown that the inhomogeneous nature of percolating gold films controls the optical properties even at such long wavelengths as 500 \ensuremath{\mu}m, where the typical grain size is 10 nm, and the effective-medium theory is shown to be invalid close to the percolation threshold.
Journal ArticleDOI
State of the Art of CT Detectors and Sources: A Literature Review
Efrat Shefer,Ami Altman,Rolf Karl Otto Behling,Raffy Goshen,Lev Gregorian,Yalon Roterman,Igor Uman,Naor Wainer,Yoad Yagil,Oren Zarchin +9 more
TL;DR: The three CT components with the greatest impact on image quality are the X-ray source, detection system and reconstruction algorithms, and this paper focuses on the first two.