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Using drawings and deep neural networks to characterize the building blocks of human visual similarity.

Early in life and without special training, human beings discern resemblance between abstract visual stimuli, such as drawings, and the real-world objects they represent. We used this capacity for visual abstraction as a tool for evaluating deep neural networks (DNNs) as models of human visual perce...

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Publicado en:Memory & Cognition Vol. 53; no. 1; pp. 219 - 242
Autores principales: Mukherjee, Kushin, Rogers, Timothy T.
Formato: Artículo
Publicado: Springer Nature Jan2025
Materias:
Task performance
Semantics
Judgment (Psychology)
Statistical models
Drawing
Statistical sampling
Convolutional neural networks
Descriptive statistics
Deep learning
Visual perception
Factor analysis
Regression analysis
Acceso en línea:Ver este registro en EBSCOhost