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  Insights from Machine Learning Applied to Human Visual Classification

Graf, A., & Wichmann, F. (2004). Insights from Machine Learning Applied to Human Visual Classification. In S. Thrun, L. Saul, & B. Schölkopf (Eds.), Advances in Neural Information Processing Systems 16: Proceedings of the 2003 Conference (pp. 905-912). Cambridge, MA, USA: MIT Press.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D8E9-7 Version Permalink: http://hdl.handle.net/21.11116/0000-0005-464B-9
Genre: Conference Paper

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 Creators:
Graf, ABA1, 2, 3, Author              
Wichmann, FA1, 3, Author              
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
3Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: We attempt to understand visual classification in humans using both psychophysical and machine learning techniques. Frontal views of human faces were used for a gender classification task. Human subjects classified the faces and their gender judgment, reaction time and confidence rating were recorded. Several hyperplane learning algorithms were used on the same classification task using the Principal Components of the texture and flowfield representation of the faces. The classification performance of the learning algorithms was estimated using the face database with the true gender of the faces as labels, and also with the gender estimated by the subjects. We then correlated the human responses to the distance of the stimuli to the separating hyperplane of the learning algorithms. Our results suggest that human classification can be modeled by some hyperplane algorithms in the feature space we used. For classification, the brain needs more processing for stimuli close to that hyperplane than for those further away.

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 Dates: 2004-06
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 2273
 Degree: -

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Title: Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003)
Place of Event: Vancouver, BC, Canada
Start-/End Date: 2003-12-08 - 2003-12-13

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Title: Advances in Neural Information Processing Systems 16: Proceedings of the 2003 Conference
Source Genre: Proceedings
 Creator(s):
Thrun, S, Editor
Saul, LK, Editor
Schölkopf, B1, Editor            
Affiliations:
1 Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794            
Publ. Info: Cambridge, MA, USA : MIT Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 905 - 912 Identifier: ISBN: 0-262-20152-6