Improving Machine Vision Using Human Perceptual Representations: The Case of Planar Reflection Symmetry for Object Classification

Achieving human-like visual abilities is a holy grail for machine vision, yet precisely how insights from human vision can improve machines has remained unclear. Here, we demonstrate two key conceptual advances: First, we show that most machine vision models are systematically different from human o...

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Vydané v:	IEEE transactions on pattern analysis and machine intelligence Ročník 44; číslo 1; s. 228 - 241
Hlavní autori:	Pramod, RT, Arun, SP
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.01.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Artificial neural networks Classification Computational modeling computational models of vision Computer vision Fixing Human performance Humans Machine vision Neural Networks, Computer Object recognition Pattern Recognition, Visual Perception perception and psychophysics Prediction algorithms Search problems Symmetry Systematic errors Systematics Task analysis Vision systems Visualization
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
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