A moving target recognition method is proposed in this paper, which is based on multi-features fusion.
本文基于多特征融合，提出了一种运动目标识别方法。
A new terrain matching neural network algorithm mode is constructed by means of multi-features fusion, which includes different statistical and geometrical features.
提出了一种多特征融合的地形匹配算法，充分利用地形的各种不同的统计特征和几何特征，构造了一种地形匹配网络模型。
In this paper, a multi focus image fusion algorithm is proposed which takes features of human vision system (HVS) into account.
本文提出了一种考虑人眼视觉系统特性的多聚焦图像融合算法。
To fuse different multi-focus images effectively, an adaptive fusion method of multi-focus images based on regional features in wavelet domain is proposed.
为了对不同的多聚焦图像进行有效融合，提出了一种小波域中基于区域特征的自适应多聚焦图像融合方法。
To get more precise fusion features by clearing redundant features, we propose a feature selection method based on multi-object evolution algorithm.
为了获得更精简的特征序列，去除冗余特征，在特征约减方面，提出了基于多目标遗传算法的虹膜融合特征约减方法；
A new terrain matching neural network algorithm mode is constructed by means of multi-feature fusion, which includes different statistical and geometrical features.
提出了基于神经网络实现多特征融合的地形匹配算法，充分利用地形的各种不同的统计特征和几何特征，构造了一种地形匹配网络模型。
A new terrain matching neural network algorithm mode is constructed by means of multi-feature fusion, which includes different statistical and geometrical features.
提出了基于神经网络实现多特征融合的地形匹配算法，充分利用地形的各种不同的统计特征和几何特征，构造了一种地形匹配网络模型。
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