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Untangling invariant object recognition

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Citation

James J. DiCarlo, David D. Cox (2007)
Untangling invariant object recognition
Trends in Cognitive Sciences 11 : 333-341
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Abstract

Despite tremendous variation in the appearance of visual objects, primates can recognize a multitude of objects, each in a fraction of a second, with no apparent effort. However, the brain mechanisms that enable this fundamental ability are not understood. Drawing on ideas from neurophysiology and computation, we present a graphical perspective on the key computational challenges of object recognition, and argue that the format of neuronal population representation and a property that we term ‘object tangling’ are central. We use this perspective to show that the primate ventral visual processing stream achieves a particularly effective solution in which single-neuron invariance is not the goal. Finally, we speculate on the key neuronal mechanisms that could enable this solution, which, if understood, would have far-reaching implications for cognitive neuroscience.

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Categories

  • gpu
  • computer vision
  • vision
  • neuroscience
  • behavior
  • rodents
  • physiology
  • methods
  • face recognition
  • computation
  • human
  • fMRI
  • faces
  • featured
  • primates
  • theory
  • simulation
  • fpga
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