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Topic modeling has been an increasingly mature method to bridge the semantic gap between the low-level features and high-level semantic information. However, with more and more high spatial resolution...
A kernel-based method for very high spatial resolution remote sensing image classification is proposed in this article. The new kernel method is based on spectral-spatial information and structure inf...
A significant portion of the world’s text is tagged by readers on social bookmarking websites. Credit attribution is an inherent problem in these corpora because most pages have multiple tags, but the...
The use of topic models to analyze domainspecific texts often requires manual validation of the latent topics to ensure that they are meaningful. We introduce a framework to support such a large-scale...
Supplementary Figure 2 shows an enlarged version of Figure 1 in the main paper with additional details in the caption.Supplementary Figure 3 shows additional data points for Figure 7 in the main paper...
Topic modeling based on latent Dirichlet allocation (LDA) has been a framework of choice to perform scene recognition and annotation. Recently, a new type of topic model called the Document Neural Aut...

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