对象(语法)
视觉对象识别的认知神经科学
人工智能
视皮层
表(数据库)
心理学
认知科学
视觉科学
计算机视觉
空格(标点符号)
计算机科学
沟通
神经科学
操作系统
数据挖掘
作者
Daniel Kaiser,Genevieve L. Quek,Radoslaw M. Cichy,Marius V. Peelen
标识
DOI:10.1016/j.tics.2019.04.013
摘要
In natural vision, objects appear at typical locations, both with respect to visual space (e.g., an airplane in the upper part of a scene) and other objects (e.g., a lamp above a table). Recent studies have shown that object vision is strongly adapted to such positional regularities. In this review we synthesize these developments, highlighting that adaptations to positional regularities facilitate object detection and recognition, and sharpen the representations of objects in visual cortex. These effects are pervasive across various types of high-level content. We posit that adaptations to real-world structure collectively support optimal usage of limited cortical processing resources. Taking positional regularities into account will thus be essential for understanding efficient object vision in the real world.
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