Abstract:Figures are an essential part of scientific communication. Yet little is understood about how accessible (e.g., color-blind safe), readable (e.g., good contrast), and explainable (e.g., contain captions and legends) they are. We develop computational techniques to measure these features and analyze a large sample of them from open access publications. Our method combines computer and human vision research principles, achieving high accuracy in detecting problems. In our sample, we estimated that around 20.6% o… Show more
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