School of Computer Science and Informatics

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Browsing School of Computer Science and Informatics by Type "Preprint"

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    An investigation into alternative methods for the defuzzification of an interval type-2 fuzzy set.
    (2006-04-24T17:26:02Z) Coupland, Simon; John, Robert, 1955-
    The number of applications of interval type-2 fuzzy logic to real world problems is growing. To date such systems have used type-reduction or an approximation of typereduction to arrive at final crisp output from the system. This paper describes the novel direct defuzzifier for interval type-2 fuzzy sets. A number of fuzzy systems are compared with direct defuzzifier. We compare each defuzzifiers output surface in a simple rule-based system. The direct defuzzifier compares favourably with the type-reduction method under the minimum t-norm. Also, we found that the non-stationary approach provided interesting results.
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    ItemEmbargo
    Validation of convolutional layers in deep learning models to identify patterns in multispectral images: Identification of palm units
    (IEEE Computer Society, 2019-07-15) Peña, Alejandro; Bonet, Isis; Manzur, Diego; Gongora, Mario Augusto; Caraffini, Fabio
    The convolutional neural networks (CNN) are considered as a particular case of the Deep Learning neural networks, and have been widely used for the extraction of features in images, audio files or text recognition. For the automatic extraction of features from multispectral images, many researchers have appealed to the use of CNN models, which integrate layers with different structures in context with the solution of a problem, which suggests quite a challenge. That is why, in this article, we propose a method to evaluate the stability in the design of convolutional layers for labeling and identification of palm cultivation units from multispectral images. The structure of the proposed convolutional layer will be given in terms of a fuzzy feature map, obtained as a result of the Cartesian product of three vegetation indices commonly used to evaluate plant vigor in this type of crops (NDVI, GNDVI, RVI), represented as compact maps (radial basis functions). The stability in the design will be given in terms of the dominance of the main diagonal that defines the structure of a convolutional layer obtained as a result of the Cartesian product of two compact maps that represent the same multispectral image.