However, DMF-based approaches face limitations when dealing with complex and nonlinear raw data. To address this issue, Auto-weighted Multi-view Deep Nonnegative Matrix Factorization with Multi-kernel ...

The findings of this paper suggest that including PET information in the kernel enhances the robustness of the reconstruction in case of spatial inconsistency. Nevertheless, accurate registration and ...

In this paper, a novel unsupervised model called kernel principal component analysis (KPCA) convolution is proposed for extracting representative features from multi-temporal VHR images. Based on the ...

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