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Gaurav Sharma
Researcher at Shenzhen University
Publications - 1520
Citations - 40824
Gaurav Sharma is an academic researcher from Shenzhen University. The author has contributed to research in topics: Medicine & Chemistry. The author has an hindex of 82, co-authored 1244 publications receiving 31482 citations. Previous affiliations of Gaurav Sharma include Northeastern University & D. E. Shaw & Co..
Papers
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Proceedings ArticleDOI
Quantification of Longitudinal Changes in Retinal Vasculature from Wide-Field Fluorescein Angiography via a Novel Registration and Change Detection Approach
TL;DR: A methodology for quantifying retinal non-perfusion by automated analysis of the FA images captured during successive clinical visits is proposed and results indicate that the proposed method provides assessments of vasculature changes that are in good agreement with the ophthalmologist-provided annotations.
Journal ArticleDOI
SwiftReg cluster registration automatically reduces flow cytometry data variability including batch effects.
TL;DR: To identify batch variation, this method registers an internal standard or consensus sample from each batch and applies the resulting registration shifts to individual samples, reducing the batch variation while preserving biological differences.
Journal ArticleDOI
Sol–gel synthesis of polyacrylamide-stannic arsenate nanocomposite ion exchanger: binary separations and enhanced photo-catalytic activity
TL;DR: In this paper, polyacrylamide-stannic arsenate nanocomposite (PA/SANC) ion exchanger has been synthesized using sol-gel technique.
Proceedings ArticleDOI
Automated Coverage Register Access Technology on UVM Framework for Advanced Verification
TL;DR: This paper focuses on advanced verification scenarios using coverage automation and Register Access Technology (RAT) on UVM verification environment and justifies the functional coverage and fast execution of verification flow as compared to conventional verification methods.
Proceedings Article
Efficient Computation of Display Gamut Volumes in Perceptual Spaces.
TL;DR: A useful representation of the gamut of an additive display that facilitates efficient numerical computation of thegamut volume is developed and several alternative numerical schemes for gamut volume computations in perceptual spaces are evaluated.