Shin’ya Nishida

Human visual grouping based on within- and cross-area temporal correlations

The paper investigates how human visual segmentation is influenced by within- and cross-area temporal correlations using a novel stimulus generation algorithm and a task-based experiment.

Psychophysical measurement of perceived motion flow of naturalistic scenes

This paper introduces a psychophysical method to measure perceived optical flow in naturalistic scenes and compares it to ground truths and models, revealing flow illusions and computational mechanisms.

GGSDT: A unified signal detection framework for confidence data analysis

This paper introduces GGSDT, a signal detection framework for analyzing confidence data, and provides an R package for its implementation.

Do training with blurred images make convolutional neural networks closer to humans concerning object recognition performance and internal representations?

This study trains CNNs on sharp and blurry images to assess if it improves object recognition robustness and internal representations, finding partial success in reducing texture bias but not achieving human-like performance.

Visual discrimination of optical material properties: a large-scale study

This study constructs a database of material images with annotated visual discrimination performance and shows that material discrimination depends on illumination and geometry, with individual differences in glossiness perception.

Haptic metameric textures

This study investigates how touch and vision process texture by comparing sensitivity to image statistics, finding that touch responds to lower-order statistics while vision detects higher-order ones.