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In this paper, we proposed a novel semi-supervised classification method with locally linear coordination for face recognition. The key idea of robust mixture modeling by t-distributions is combined with probabilistic subspace mixture models. It solves the robustness problems of locally linear coordination, by introducing a weighted reformulation of the embedding step. Comparison experiments between...
Polarization decomposition is an important approach for polarimetric SAR image classification. In this paper, decomposition methods with different data format are discussed. Especially, A new decomposition method which is Krogagger decomposition with T matrix is proposed. Simulation results show that decompositions with T matrix have less speckle.
In this paper, we proposed a novel semi-supervised classification method with path-based similarity measure for face recognition. Based on the manifold assumption, our method can reflect genuine similarities between data points on manifolds without any other additional knowledge, which takes into account the existence of noise and outliers in the face dataset. Comparison experiments between the proposed...
In this paper, a novel method, which combines subaperture decomposition with H/alpha/Wishart classifier, is introduced to classify polarimetric synthetic radar (SAR) images. We use H/alpha plane to initially classify the full-resolution polarimetric SAR image. The initial classification map defines training sets for classification based on coherency matrices of subapertures and wishart distribution...
Polarimetric SAR image classification is an important research area. Various classification methods continue to be developed for specific applications. In this paper, A new unsupervised classification method for polarimetric SAR images is proposed. It is based on independent component analysis (ICA). By ICA processing, several independent components are extracted from the channels of the SAR images...
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