机译:基于多源数据融合和基于Fisher标准的最近特征空间的滑坡分类方法
Dept. of Electr. Eng., Nat. Taipei Univ. of Technol., Taipei, Taiwan;
feature extraction; geomorphology; geophysical image processing; hazards; image capture; image classification; image fusion; land cover; remote sensing; Earth remote sensing; FCNFS approach; FCNFS classifier; Fisher criterion-based nearest feature space approach; NFS algorithm; Taiwan; band generation process; between-class discrimination; classifier enhancement; land cover classification; landslide classification; landslide hazard assessment; multiple adaptive BGP; multisource data fusion; multisource image supervised classification; multispectral images; remotely sensed image fusion; within-class discrimination; Accuracy; Data integration; Earth; Image resolution; Remote sensing; Terrain factors; Training; Band generation process (BGP); Fisher criterion; classification; landslide; multisource data fusion; nearest feature space (NFS);
机译:基于广义正布尔函数的滑坡分类多源数据融合
机译:校准电动机图像中的EEG功能,使用多源融合传输学习的少量当前数据
机译:高维数据集的改进的最近特征空间方法
机译:使用基于Fisher准则的最近特征空间方法进行图像分类的多源数据融合
机译:通过多源分类明显融合了一种新的模糊统计方法。
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