The basis of report-difference superiority in delayed perceptual comparison tasks

2020 ◽  
Vol 48 (5) ◽  
pp. 856-869
Author(s):  
Michael Pilling ◽  
Douglas J.K. Barrett ◽  
Angus Gellatly
Keyword(s):  
Perceptual Comparison

scholarly journals Perceptual Comparison of Procedural and Data-Driven Eye Motion Jitter

2019 ◽  
Author(s):  
Sophie Jörg ◽  
Andrew T. Duchowski ◽  
Krzysztof Krejtz ◽  
Anna Niedzielska
Keyword(s):  
Data Driven ◽  
Eye Motion ◽  
Perceptual Comparison

scholarly journals Perceptual Comparison of Source-Code Plagiarism within Students from UK, China, and South Cyprus Higher Education Institutions

2017 ◽  
Vol 17 (2) ◽  
pp. 1-16 ◽  
Author(s):  
Georgina Cosma ◽  
Mike Joy ◽  
Jane Sinclair ◽  
Margarita Andreou ◽  
Dongyong Zhang ◽  
...  
Keyword(s):  
Higher Education ◽  
Higher Education Institutions ◽  
Source Code ◽  
Perceptual Comparison

A perceptual comparison: Stuttering and nonstuttering children's nonstuttered speech

1983 ◽  
Vol 8 (4) ◽  
pp. 283-290 ◽  
Author(s):  
Carol MacIndoe Krikorian ◽  
Charles M. Runyan
Keyword(s):  
Perceptual Comparison

Ratios and differences in perceptual comparison: A reexamination of Torgerson’s conjecture

2018 ◽  
Vol 85 ◽  
pp. 62-75 ◽  
Author(s):  
Randolph C. Grace ◽  
Nicola J. Morton ◽  
Matthew D. Ward ◽  
Anna J. Wilson ◽  
Simon Kemp
Keyword(s):  
Perceptual Comparison

Physical and Perceptual Comparison of Real and Focused Sound Sources in a Concert Hall

2016 ◽  
Vol 64 (12) ◽  
pp. 1014-1025
Author(s):  
Sebastià V. Amengual Garí ◽  
Jukka Pätynen ◽  
Tapio Lokki
Keyword(s):  
Sound Sources ◽  
Concert Hall ◽  
Perceptual Comparison

Nonlinear Diffusion Model for Fabric Image Denoising

2012 ◽  
Vol 627 ◽  
pp. 484-488
Author(s):  
Da Li Chen ◽  
Ding Yu Xue ◽  
Yang Quan Chen
Keyword(s):  
Image Denoising ◽  
Diffusion Model ◽  
Nonlinear Diffusion ◽  
Diffusion Models ◽  
Perceptual Comparison

In this paper, five nonlinear diffusion models for fabric image denoising are introduced. The advantages and drawbacks of these five models are described through describing their implementation methods. Quantitative and perceptual comparison experiments are given to verify the performance of these methods. Finally some valuable conclusions about denoising performance of these five models are present which is helpful for choosing and using these models in fabric image denoising.

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