학술논문
A neural network architecture for generalized category perception
Document Type
Conference
Author
Source
Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94) Neural networks Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on. 5:3024-3029 vol.5 1994
Subject
Language
Abstract
The recognition of objects given a complete or partial set of features is inherent in human intelligence. The fields of pattern recognition and artificial intelligence, among others, have addressed this topic with a variety of models which lack consistency and generality. Thus, it is the goal of this paper to set forth a generalized model for object recognition (classification). System models utilizing neural networks have been suggested for category perception. The proposed system is based on the principles of probability. We refer to this architecture as the generalized category perception model.ETX