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Texture analysis using income inequality metrics
2014 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, 2014Texture analysis on digital images can be used to correctly segment areas of an image and/or classify different objects within the field of view of a digital camera. Depending on the application, one can use a Gray Level Co-occurrence Matrix (GLCM) to detect patterns or a simple contrast measure such as variance can be a good metric as well.
Gabriel Thomas, Manickavasagan Annamalai
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Texture features based on the use of the hough transform and income inequality metrics
2017 Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA), 2017Texture analysis of digital images has potential applications to image segmentation and classification. The quality of texture features can significantly determine the outcome of these two important applications. For images that consist of textures defined as patterns of straight lines, the use of features extracted using the Gray Level Co-occurrence ...
Husam Elsaid +2 more
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Income Inequality Metrics: Understanding the Issues and Concerns in Inequality Measurement
SSRN Electronic Journal, 2015The essay deals with the definition of inequality, the problems and principles of any inequality measurement. Then it goes on to understand various measurement indices of inequality, their comparative advantages and disadvantages. Finally, it seeks to understand the significance of having inequality measured and compared.
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Assessment methods and performance metrics for redox flow batteries
Nature Energy, 2021Yang Shi, Yi-Chun Lu
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Risk assessment of microplastic particles
Nature Reviews Materials, 2022Albert A Koelmans +2 more
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Gas diffusion electrodes, reactor designs and key metrics of low-temperature CO2 electrolysers
Nature Energy, 2022David W Wakerley +2 more
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