視覚系における動的な群化過程のニューラルネットワークモデル

概要

論文の詳細を見る
The mechanism underlying perceptual grouping of visual stimuli is not static, but dynamic. In this paper, the dynamical grouping process is implemented with a neural network model consisting of an array of(hyper)columns suggested by Hubel & Wiesel, where intracolumnar inhibition and intercolumnar facilitation are incorporated. The model was applied successfully to figures consisting of a set of points yielding either of two ways of groupings from time to time due to neural fatigue. Then the model was extended to introduce dependency on fixation points as well as neural fatigue and then applied to the Necker Cube. The model output either of two ways of 3D interpretations depending on the fixation points.
社団法人映像情報メディア学会の論文
1999-01-20