ISSN:
1432-0770
Source:
Springer Online Journal Archives 1860-2000
Topics:
Biology
,
Computer Science
,
Physics
Notes:
Abstract This paper describes a model of a neural visual system of a higher animal, in which the capability of pattern recognition develops adaptively. To produce the adaptability, we adopted “self-organizing cells,” and with them modeled feature-detecting cells which were discovered by Hubel and Wiesel and whose plasticity was found by Blakemore and Cooper. Combining the “self-organizing cells” and the learning principle of a Perceptron-type system, we constructed a model of the whole visual system. The model is also equipped with an eye movement control mechanism for gazing, which reduces the number of “selforganizing cells” required for pattern recognition, thus contributing to their quick self-organization. Computer simulation and an experiment using a hardware simulator showed that “self-organizing cells” quickly become sensitive to the features often seen and that the resulted system can classify patterns with a rather small number of feature-detecting cells.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF00207287
