Grossberg S, Mingolla E, Todorović D
IEEE Trans Biomed Eng. 1989 Jan;36(1):65-84. doi: 10.1109/10.16450.
Recent results towards development of a neural network architecture for general-purpose preattentive vision are summarized. The architecture contains two parallel subsystems, the boundary contour system (BCS) and the feature contour system (FCS), which interact together to generate a representation of form-and-color-and-depth. Emergent boundary segmentation within the BCS and featural filling-in within the FCS are herein emphasized within a monocular setting. Applications to the analysis of boundaries, textures, and smooth surfaces are described, as is a model for invariant brightness perception under variable illumination conditions. The theory shows how suitably defined parallel and hierarchical interactions overcome computational uncertainties that necessarily exist at early processing stages. Some of the psychophysical and neurophysiological data supporting the theory's predictions are mentioned.
本文总结了近期在开发用于通用前注意视觉的神经网络架构方面取得的成果。该架构包含两个并行子系统，即边界轮廓系统（BCS）和特征轮廓系统（FCS），它们相互作用以生成形状、颜色和深度的表示。本文在单眼环境下强调了BCS内的新兴边界分割和FCS内的特征填充。描述了其在边界、纹理和平滑表面分析中的应用，以及一个在可变光照条件下不变亮度感知的模型。该理论展示了适当定义的并行和分层交互如何克服早期处理阶段必然存在的计算不确定性。文中还提到了一些支持该理论预测的心理物理学和神经生理学数据。
