@inproceedings{e51f1c0515cc47319219c4568ca7be36,
title = "Effectiveness of spectral band selection/extraction techniques for spectral data",
abstract = "In the past few years a variety of successful algorithms to select/extract discriminative spectral bands was introduced. By exploiting the connectivity of neighbouring spectral bins, these techniques may be more beneficial than the standard feature selection/extraction methods applied for spectral classification. The goal of this paper is to study the effect of the training sample size on the performance of different strategies to select/extract informative spectral regions. We also consider the success of these methods compared to Principal Component Analysis (PCA) for different numbers of extracted components/groups of spectral bands.",
keywords = "conference contrib. refereed, CWTS 0.75 <= JFIS < 2.00",
author = "M Skurichina and S Verzakov and P Paclik and RPW Duin",
year = "2006",
language = "Undefined/Unknown",
isbn = "3-540-37236-9",
publisher = "Springer",
pages = "541--550",
editor = "DY Yeung and JT Kwok and A Fred and F Roli and {de Ridder}, D",
booktitle = "Structural, syntactic and statistical pattern recognition",
note = "Joint IAPR International Workshops SSPR 2006 and SPR 2006, Hong Kong, China ; Conference date: 17-08-2006 Through 19-08-2006",
}