Lúcio André de Castro Jorge

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Atomic Force Microscopy (AFM) can be used to obtain high-resolution topographical images of bacteria revealing surface details and cell integrity. During scanning however, the interactions between the AFM probe and the membrane results in distortion of the images. Such distortions or artifacts are the result of geometrical effects related to bacterial cell(More)
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—This paper presents a new data-mining aproach of feature subset selection as a fusion technique to automatically and optimally configure an insects behavior identifier. It is accomplished by a fusion of video and sounds directly under the space of attributes. Harris detection was used as insect tracking, as well as Wavelet-Multifractal as sound analysis.(More)
The goal of this paper was to apply data mining subset selection techniques and wavelet-multifractal to describe insect behavior. It was proposed wavelet modulus maxima to extract multifractal parameters of sound attributes for pattern recognition of an insect behavior. Wrapper data mining approach was used to select relevant attributes. It has been found(More)
The choice of a color model is of great importance for many computer vision algorithms. However, there are many color models available; the inherent difficulty is how to automatically select a single color model or, alternatively, a subset of features from several color models producing the best result for a particular task. To achieve proper colors(More)
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