Now showing items 1-2 of 2

  • Experimental comparison of support vector machines with random forests for hyperspectral image land cover classification 

    Marwala, T.; Abe, B. T.; Olugbara, Oludayo O. (Indian Academy of Scienceshttp://download.springer.com/static/pdf/252/art%253A10.1007%252Fs12040-014-0436-x.pdf?auth66=1408093933_acb520a22c71dc468fdc1783b80c6c0b&ext=.pdf, 2014-06-12)
    The performances of regular support vector machines and random forests are experimentally com-pared for hyperspectral imaging land cover classification. Special characteristics of hyperspectral imaging dataset present diverse ...
  • Hyperspectral image classification using random forests and neural networks 

    Abe, B. T.; Olugbara, Oludayo O.; Marwala, T. (International Association of Engineers, 2012)
    Spectral unmixing of hyperspectral images are based on the knowledge of a set of unknown endmembers. Unique characteristics of hyperspectral dataset enable different processing problems to be resolved using robust ...