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  Learning to use informative features in shape categorisation

Tanner, T. (2006). Learning to use informative features in shape categorisation. Poster presented at 29th European Conference on Visual Perception (ECVP 2006), St. Petersburg, Russia.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D0AD-4 Version Permalink: http://hdl.handle.net/21.11116/0000-0004-B660-2
Genre: Poster

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 Creators:
Tanner, TG1, 2, Author              
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: The aim of the study was to find out how humans learn to use informative features to categorise novel objects. Subjects were presented with a sequence of shapes, which they had to learn to classify into two categories. Immediate feedback about the true category was given after each trial. Stimuli consisted of large irregularly shaped contours containing several protrusions ('features'), whose curvatures varied stochastically from trial to trial. The exemplars for each class were drawn from partially overlapping Gaussian distributions in a multi-dimensional feature space. Thus, a single feature alone was often not sufficient to discriminate between classes and exemplars could be ambiguous. The features were independent and varied in diagnosticity (d') and perceptual discriminability. Importantly, the stimulus design made it possible to use eye-movement recordings to measure which features subjects looked at to perform the task. The results show that humans can learn to discriminate stochastic categories despite the inherent ambiguity of the task, and that with increasing expertise the fixations become more focused possibly reflecting the subject's belief about relevant features. The human data (performance, reaction times, and eye movements) are compared with an ideal observer and a variety of rational (Bayesian) learner models.

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 Dates: 2006-08
 Publication Status: Published in print
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1177/03010066060350S101
BibTex Citekey: Tanner2006
 Degree: -

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Title: 29th European Conference on Visual Perception (ECVP 2006)
Place of Event: St. Petersburg, Russia
Start-/End Date: 2006-08-20 - 2006-08-26

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Title: Perception
Source Genre: Journal
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Publ. Info: London : Pion Ltd.
Pages: - Volume / Issue: 35 (ECVP Abstract Supplement) Sequence Number: - Start / End Page: 41 Identifier: ISSN: 0301-0066
CoNE: https://pure.mpg.de/cone/journals/resource/954925509369