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Dream Formulations and Deep Neural Networks: Humanistic Themes in the Iconology of the Machine-Learned Image
[article]
2018
arXiv
pre-print
This paper addresses the interpretability of deep learning-enabled image recognition processes in computer vision science in relation to theories in art history and cognitive psychology on the vision-related perceptual capabilities of humans. Examination of what is determinable about the machine-learned image in comparison to humanistic theories of visual perception, particularly in regard to art historian Erwin Panofsky's methodology for image analysis and psychologist Eleanor Rosch's theory
arXiv:1802.01274v1
fatcat:ndfkatx74zeqnbfzklwzy2k4my