Throwing Down the Visual Intelligence Gauntlet
Name
MIT-CSAIL-TR-2012-016.pdf
Size
560.52 KB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Tan, Cheston
Leibo, Joel Z
Poggio, Tomaso
Advisor(s)
Tomaso Poggio
Date Issued
2012
Citation
Machine Learning for Computer Vision (2012); eds: Cipolla R, Battiato S, Giovanni Maria F. Springer: Studies in Computational Intelligence Vol. 411.
Series/Report no.
MIT-CSAIL-TR-2012-016
CBCL-309
Abstract
In recent years, scientific and technological advances have produced artificial systems that have matched or surpassed human capabilities in narrow domains such as face detection and optical character recognition. However, the problem of producing truly intelligent machines still remains far from being solved. In this chapter, we first describe some of these recent advances, and then review one approach to moving beyond these limited successes---the neuromorphic approach of studying and reverse-engineering the networks of neurons in the human brain (specifically, the visual system). Finally, we discuss several possible future directions in the quest for visual intelligence.
Subjects
Vision
Artificial intelligence
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported
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