An experimental comparison of RGB, YIQ, LAB, HSV, and opponent color models

1987 ◽  
Vol 6 (2) ◽  
pp. 123-158 ◽  
Author(s):  
Michael W. Schwarz ◽  
William B. Cowan ◽  
John C. Beatty
Keyword(s):  
Experimental Comparison ◽  
Color Models ◽  
Opponent Color

scholarly journals Opponent-color models and the influence of rod signals on the loci of unique hues

2000 ◽  
Vol 40 (24) ◽  
pp. 3333-3344 ◽  
Author(s):  
Steven L Buck ◽  
Roger F Knight ◽  
John Bechtold
Keyword(s):  
Color Models ◽  
Opponent Color ◽  
Unique Hues

How to Measure Discount Rates? An experimental comparison of three methods

2010 ◽  
Author(s):  
David J. Hardisty ◽  
Katherine J. Thompson ◽  
David H. Krantz ◽  
Elke U. Weber
Keyword(s):  
Experimental Comparison ◽  
Discount Rates

Analysis of athletes’ stadium stress source based on improved layered K-means algorithm

2020 ◽  
Vol 39 (4) ◽  
pp. 5905-5914
Author(s):  
Chen Gong
Keyword(s):  
Experimental Data ◽  
Machine Learning Algorithms ◽  
User Preference ◽  
Experimental Comparison ◽  
Actual Situation ◽  
Medical Field ◽  
Pressure Source ◽  
Preference Model ◽  
Related Research ◽  
Analysis System

Most of the research on stressors is in the medical field, and there are few analysis of athletes’ stressors, so it can not provide reference for the analysis of athletes’ stressors. Based on this, this study combines machine learning algorithms to analyze the pressure source of athletes’ stadium. In terms of data collection, it is mainly obtained through questionnaire survey and interview form, and it is used as experimental data after passing the test. In order to improve the performance of the algorithm, this paper combines the known K-Means algorithm with the layering algorithm to form a new improved layered K-Means algorithm. At the same time, this paper analyzes the performance of the improved hierarchical K-Means algorithm through experimental comparison and compares the clustering results. In addition, the analysis system corresponding to the algorithm is constructed based on the actual situation, the algorithm is applied to practice, and the user preference model is constructed. Finally, this article helps athletes find stressors and find ways to reduce stressors through personalized recommendations. The research shows that the algorithm of this study is reliable and has certain practical effects and can provide theoretical reference for subsequent related research.

EXPERIMENTAL COMPARISON OF LOOP HEAT PIPE PERFORMANCE WITH VARIOUS EVAPORATOR DESIGNS

2014 ◽  
Vol 5 (1-4) ◽  
pp. 287-294
Author(s):  
S. Ouenzerfi ◽  
T. Barreteau ◽  
C. Petit ◽  
Valerie Sartre ◽  
Jocelyn Bonjour ◽  
...  
Keyword(s):  
Heat Pipe ◽  
Experimental Comparison ◽  
Loop Heat Pipe
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