Classifying objects in constellation images.

<p>a) Sample images from the original Fashion MNIST and MNIST datasets along with their constellations version below them. b) The plot shows the comparable classification accuracy of Humans and GenSearch algorithm on a test set of 38 images on both datasets c). Confusion matrix for classificat...

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Bibliographic Details
Main Author:	Tarun Khajuria (12117309) (author)
Other Authors:	Kadi Tulver (17892256) (author), Jaan Aru (3747808) (author)
Published:	2025
Subjects:	Genetics Science Policy Mental Health Hematology Biological Sciences not elsewhere classified Information Systems not elsewhere classified solving task inspired results shed light level cues based interpreting sensory input enables robust perception framing visual inference candidate solutions compared complex problem solving visual problem solving generative search models generative search algorithm visual problem suitable solutions generative model test images structural fitness star constellations reaction time rapid adaptation possible mechanisms passive process often described noisy data interpret ambiguous inferred signals human vision human experiments examining factors emulate aspects distribution inputs discriminative components dataset serves computational model computational implementation ambiguous conditions also function
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Classifying objects in constellation images.

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