Lateral Inhibition Pyramidal Neural Network for Image Classification
Lateral Inhibition Pyramidal Neural Network for Image Classification
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DOI：
10.1109/tcyb.2013.2240295
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发表时间：
2013-12-01
影响因子：
11.8
通讯作者：
Ren, Tsang Ing
中科院分区：
文献类型：
--
作者：
Fernandes, Bruno Jose Torres;Cavalcanti, George D. C.;Ren, Tsang Ing
人类的视觉系统是中枢神经系统中最迷人和最复杂的机制之一，它使我们能够看到东西。正是通过视觉系统，我们能够完成从最简单的任务，如物体识别到最复杂的视觉解释、理解和感知。受这一复杂系统的启发，提出了两种基于人类视觉系统特性的模型。这些模型是基于接受场和抑制场的概念而设计的。第一个模型是具有侧抑制的金字塔神经网络，称为侧抑制金字塔神经网络。第二种模型是一种有监督的图像分割系统，称为基于感受野的分割和分类。这项工作表明，这两个模型的结合是有益的，所获得的结果比其他先进的方法更好。
The human visual system is one of the most fascinating and complex mechanisms of the central nervous system that enables our capacity to see. It is through the visual system that we are able to accomplish from the most simple task such as object recognition to the most complex visual interpretation, understanding and perception. Inspired by this sophisticated system, two models based on the properties of the human visual system are proposed. These models are designed based on the concepts of receptive and inhibitory fields. The first model is a pyramidal neural network with lateral inhibition, called lateral inhibition pyramidal neural network. The second proposed model is a supervised image segmentation system, called segmentation and classification based on receptive fields. This work shows that the combination of these two models is beneficial, and the results obtained are better than that of other state-of-the-art methods.