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Computational modeling of human reasoning processes for interpretable visual knowledge: a case study with radiographers
Article proposing a computational method to quantify and dissect visual reasoning. The method characterizes spatial and temporal features and identifies common and contrast visual reasoning patterns to extract significant gaze activities. The visual reasoning patterns are explainable and can be compared among different groups to discover strategy differences. Empirical observations show that the method can capture the temporal and spatial features of human visual attention and distinguish expertise level. By revealing task-related reasoning processes, this method demonstrates potential for explaining human visual understanding.
Date:
December 10, 2020
Creator:
Li, Yuan; Cao, Hongfei; Allen, Carla M.; Wang, Xin; Erdelez, Sanda & Shyu, Chi-Ren
System:
The UNT Digital Library