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Learning to see faces and objects

delete2003-01-01
delete101
PRE
AI
M
Michael J. Tarr
C
Cheng, YD
DOI：10.1016/S1364-6613(02)00010-4delete
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Abstract

Abstract

En 中文
Visual recognition of objects is an impressively difficult problem that biological systems solve effortlessly. We consider two aspects of this ability. First, is the recognition of all objects accomplished by either a single system or multiple, domain-specific systems? Behavioral, neuropsychological and neuroimaging data indicate that a single system is sufficient for the recognition of all objects at all levels. Second, how does such a system 'tune' itself to the constraints imposed by recognition at different levels of specificity? Evidence indicates that the task demands and learning that arise from different forms of feedback determine which computational routines are recruited automatically in object recognition.
Keywords:
3-DIMENSIONAL OBJECTS
VIEWPOINT INVARIANCE
NATURAL CATEGORIES
ROTATED OBJECTS
TEMPORAL CORTEX
RECOGNITION
EXPERTISE
LEVEL
AREA
PERCEPTION
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Trends in Cognitive Sciences cover
Trends in Cognitive Sciences
IF:
17.2
Papers:
3.6K
Citations:
3.5W

Organization

No organization information available