392 research outputs found

    DS 677: Deep Learning

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    DS 636: Data Analytics with R Programming

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    DS 636-101: Data Analytics with R Program

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    ISBDD model for classification of hyperspectral remote sensing imagery

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    The diverse density (DD) algorithm was proposed to handle the problem of low classification accuracy when training samples contain interference such as mixed pixels. The DD algorithm can learn a feature vector from training bags, which comprise instances (pixels). However, the feature vector learned by the DD algorithm cannot always effectively represent one type of ground cover. To handle this problem, an instance space-based diverse density (ISBDD) model that employs a novel training strategy is proposed in this paper. In the ISBDD model, DD values of each pixel are computed instead of learning a feature vector, and as a result, the pixel can be classified according to its DD values. Airborne hyperspectral data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor and the Push-broom Hyperspectral Imager (PHI) are applied to evaluate the performance of the proposed model. Results show that the overall classification accuracy of ISBDD model on the AVIRIS and PHI images is up to 97.65% and 89.02%, respectively, while the kappa coefficient is up to 0.97 and 0.88, respectively

    Dust Extinction of Gamma-ray Burst Host Galaxies: Identification of Two Classes?

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    Dust in the host galaxies of gamma-ray bursts (GRBs) dims and reddens their afterglow spectra. Knowledge of the nature of this dust is crucial for correcting for extinction, providing clues to the nature of GRB progenitors, and probing the interstellar medium of high-redshift galaxies as well as the nature of cosmic dust when the universe was much younger and galaxies were much less evolved. The dust and extinction properties of GRB host galaxies are still poorly known. Unlike previous work, we derive in this Letter the extinction curves for 10 GRB host galaxies without a priori assumption of any specific extinction types (such as that of the Milky Way, or the Small/Large Magellanic Clouds). It is found that there appears to exist two different types of extinction curves: one is relatively flat and gray, the other displays a steeper dependence on inverse wavelength, closely resembling that of the Milky Way but with the 2175\Angstrom feature removed.Comment: 15 pages, 3 figures. Substantially revised with the same arguments; accepted for publication in The Astrophysical Journal Letter
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