Recently, feature maps have been applied to various problem domains. The success of some of these applications critically depends on whether feature maps are topologically ordered. In this paper, we propose a novel me...
详细信息
Recently, feature maps have been applied to various problem domains. The success of some of these applications critically depends on whether feature maps are topologically ordered. In this paper, we propose a novel measure for quantifying the neighborhood preserving property of feature maps. Two data sets were tested to illustrate the performance of the proposed method.
A new facial image morphing algorithm based on the Kohonen self-organizing feature map (som) algorithm is proposed to generate a smooth 2D transformation that reflects anchor point correspondences. Using only a 2D fac...
详细信息
A new facial image morphing algorithm based on the Kohonen self-organizing feature map (som) algorithm is proposed to generate a smooth 2D transformation that reflects anchor point correspondences. Using only a 2D face image and a small number of anchor points, we show that the proposed morphing algorithm provides a powerful mechanism for processing facial expressions.
Unconstrained handwritten numeral recognition using self-organizing maps (som), and self-organizing principal component analysis (PCA) is presented in this paper. In the feature-extraction phase, we develop the method...
详细信息
ISBN:
(纸本)7505338900
Unconstrained handwritten numeral recognition using self-organizing maps (som), and self-organizing principal component analysis (PCA) is presented in this paper. In the feature-extraction phase, we develop the methods to acquire nonlinear normalization of the numeral image. In the classifying phase, we construct the classifier by two layers: PCA and som. To acquire the ability, of real-time self-learning, the algorithm of PCA and som are combined together, just as their combination in structure. Experiments on 48000 handwritten numerals show that our technique achieves satisfactory results in terms of classification accuracy and time.
暂无评论