publication . Preprint . 2018

Rapid de novo shape encoding: a challenge to connectionist modeling

Greene, Ernest;
Open Access English
  • Published: 07 Jan 2018
Abstract
Neural network (connectionist) models are designed to encode image features and provide the building blocks for object and shape recognition. These models generally call for: a) initial diffuse connections from one neuron population to another, and b) training to bring about a functional change in those connections so that one or more high-tier neurons will selectively respond to a specific shape stimulus. Advanced models provide for translation, size, and rotation invariance. The present discourse notes that recent work on human perceptual skills has demonstrated immediate encoding of unknown shapes that were seen only once. Further, the perceptual mechanism pr...
Subjects
free text keywords: Quantitative Biology - Neurons and Cognition
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