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The large number of spectral bands in hyperspectral images provides abundant information to distinguish different land covers. However, these spectral bands have much redundancy and bring an extra computational burden. Thus, band selection is important for hyperspectral images. Since the labeled samples are difficult to obtain, a semi-supervised criterion based on maximum discrimination and information...
We persent a new method for performing bands secelction exptements with 16 narrow-bands multispectal images data of cucumber. This method allows for the visual inspection base on the brightness value of the images which achieve standard assessment during visual wavelength region. It follows a standard feature selection approach in which correlative coefficient measure is used as a figure of merit...
One important prerequisite for improving the level of university interdisciplinary is to establish a comprehensive evaluation system for the evaluation of existing interdisciplinary. A comprehensive evaluation system including ten indices was built based on the analysis of interdisciplinary construction in college. On the basis of this evaluation system, it analyzes the interdisciplinary level of...
This paper analyzes the drawbacks of traditional principal component analysis (PCA) firstly, and discusses the kernel principal component analysis (KPCA) as well as its drawbacks of high complexity secondly. Then it proposes the K-PCA method. Comparing with KPCA, the method proposed in this paper could achieve dimensionality reduction with faster speed. The results show that: the proposed method performs...
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