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  Towards Artificial Systems: What Can We Learn from Human Perception?

Bülthoff, H., & Chuang, L. (2010). Towards Artificial Systems: What Can We Learn from Human Perception? In B.-T. Zhang, & M. Orgun (Eds.), PRICAI 2010: Trends in Artificial Intelligence (pp. 1-3). Berlin, Germany: Springer.

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 Creators:
Bülthoff, HH1, 2, Author           
Chuang, LL1, 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: Research in learning algorithms and sensor hardware has led to rapid advances in artificial systems over the past decade. However, their performance continues to fall short of the efficiency and versatility of human behavior. In many ways, a deeper understanding of how human perceptual systems process and act upon physical sensory information can contribute to the development of better artificial systems. In the presented research, we highlight how the latest tools in computer vision, computer graphics, and virtual reality technology can be used to systematically understand the factors that determine how humans perform in realistic scenarios of complex task-solving.

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 Dates: 2010-09
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1007/978-3-642-15246-7_1
BibTex Citekey: 6656
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Title: 11th Pacific Rim International Conference on Artificial Intelligence
Place of Event: Daegu, South Korea
Start-/End Date: 2010-08-30 - 2010-09-02

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Title: PRICAI 2010: Trends in Artificial Intelligence
Source Genre: Proceedings
 Creator(s):
Zhang, B-T, Editor
Orgun, MA, Editor
Affiliations:
-
Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1 - 3 Identifier: ISBN: 978-3-642-15246-7

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Title: Lecture Notes in Computer Science
Source Genre: Series
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Pages: - Volume / Issue: 6230 Sequence Number: - Start / End Page: - Identifier: -