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- W2917509272 abstract "Remote-sensing focusing on image classification knows a large progress and receives the attention of the remote-sensing community day by day. Combining many kinds of extracted features has been successfully applied to High resolution urban satellite images using support vector machine (SVM). In this paper, we present a methodology that is promoting a performed classification by using pixel-wise SURF description features combined with spectral information in Cielab space for the first time on common scenes of urban imagery. The proposed method gives a promising classification accuracy when compared with the two types of features used separately." @default.
- W2917509272 created "2019-03-02" @default.
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- W2917509272 date "2018-10-24" @default.
- W2917509272 modified "2023-10-02" @default.
- W2917509272 title "SVM-based classification of High resolution Urban Satellites Images using Dense SURF and Spectral Information" @default.
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- W2917509272 doi "https://doi.org/10.1145/3289402.3289502" @default.
- W2917509272 hasPublicationYear "2018" @default.
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