Emily J. A-Izzeddin

The paper investigates how humans classify novel objects by combining component features, showing that a Bayesian classifier can predict classification performance based on part labels.

The paper shows that low-level image features predict perceived similarity between naturalistic scene regions, supporting the role of basic visual features in scene organization.

This study investigates orientation adaptation during naturalistic film viewing and finds stronger adaptation to cardinal orientations but weaker overall effects compared to standard tilt-aftereffect paradigms.

This study shows that confidence in perceptual decisions is influenced by natural image statistics, using a novel psychophysical paradigm.

The paper investigates how perceptual inferences balance long-term scene priors and immediate contextual information using naturalistic stimuli and a perceptual inference task.