Contextual associations represented both in neural networks and human behavior.

ABSTRACT: Contextual associations facilitate object recognition in human vision. However, the role of context in artificial vision remains elusive as does the characteristics that humans use to define context. We investigated whether contextually related objects (bicycle-helmet) are represented more similarly in convolutional neural networks (CNNs) used for image understanding than unrelated objects (bicycle-fork). Stimuli were of objects against a white background and consisted of a diverse set of contexts (N = 73). CNN representations of contextually related objects were more similar to one another than to unrelated objects across all CNN layers. Critically, the similarity found in CNNs correlated with human behavior across multiple experiments assessing contextual relatedness, emerging significan

SUBMITTER: Aminoff EM 

PROVIDER: S-EPMC8976848 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature