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• W2766705951 abstract "A new feature selection technique is proposed to address the main difficulty of hyperspectral data processing, which is related to high redundancy of data and the curse of dimensionality. The new approach is based on a new binary optimization method named Binary Fractional Order Darwinian Particle Swarm Optimization (BFODPSO) and Support Vector Machine (SVM). Then, an application of the proposed feature selection approach is taken into account in order to solve the main shortcomings of using attribute profile for extracting spatial information from the input data. Results confirm the capability of the new method for handling very high dimensional data." @default.
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• W2766705951 date "2014-06-01" @default.
• W2766705951 modified "2023-09-23" @default.
• W2766705951 title "FODSPO based feature selection for hyperspectral remote sensing data" @default.
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• W2766705951 doi "https://doi.org/10.1109/whispers.2014.8077613" @default.
• W2766705951 hasPublicationYear "2014" @default.
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