7 resultados para FRACTAL DESCRIPTORS

em Repositório da Produção Científica e Intelectual da Unicamp


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Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

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Transfer of reaction products formed on the surfaces of two mutually rubbed dielectric solids makes an important if not dominating contribution to triboelectricity. New evidence in support of this statement is presented in this report, based on analytical electron microscopy coupled to electrostatic potential mapping techniques. Mechanical action on contacting surface asperities transforms them into hot-spots for free-radical formation, followed by electron transfer producing cationic and anionic polymer fragments, according to their electronegativity. Polymer ions accumulate creating domains with excess charge because they are formed at fracture surfaces of pulled-out asperities. Another factor for charge segregation is the low polymer mixing entropy, following Flory and Huggins. The formation of fractal charge patterns that was previously described is thus the result of polymer fragment fractal scatter on both contacting surfaces. The present results contribute to the explanation of the centuries-old difficulties for understanding the triboelectric series and triboelectricity in general, as well as the dissipative nature of friction, and they may lead to better control of friction and its consequences.

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Descriptors in multivariate image analysis applied to quantitative structure-activity relationship (MIA-QSAR) are pixels of bidimensional images of chemical structures (drawings), which were used to model the trichomonicidal activities of a series of benzimidazole derivatives. The MIA-QSAR model showed good predictive ability, with r², q² and r val. ext.² of 0.853, 0.519 and 0.778, respectively, which are comparable to the best values obtained by CoMFA e CoMSIA for the same series. A MIA-based analysis was also performed by using images of alphabetic letters with the corresponding numeric ordering as dependent variables, but no correlation was found, supporting that MIA-QSAR is not arbitrary.

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This paper describes a method for leaf vein shape characterization using Hermite polynomial cubic representation. The elements associated with this representation are used as secondary vein descriptors and their discriminatory potential are analyzed based on the identification of two legume species (Lonchocarpus muehlbergianus Hassl. and L. subglaucescens Mart, ex Benth.). The elements of Hermite geometry influence a curve along all its extension allowing a global description of the secondary vein course by a descriptor of low dimensionality. The obtained results shown the analyzed species can be discriminated by this method and it can be used in addition to commonly considered elements in the taxonomic process.

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The main objective of this work is to discuss the notion of metalanguage concerning the use of thesaurus (symbols systems, functions indicators, descriptors) utilized by indexers for article representation in computerized bibliographical databases. Our corpus comprises article abstracts and bibliographical database descriptors LILACS (Literatura Latino-Americana em Ciências da Saúde) and SOCIOFILE Sociological Abstracts. We aim at clarifying the effects of subjectivity in the functioning of indexing taking account the grounds for interpretation that allow different meanings.

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Easter egg is a popular chocolate-candy in egg form commercialized in Brazil during Easter time. In this research, Quantitative Descriptive Analysis was applied to select sensory attributes which best define the modifications in appearance, aroma, flavor and texture when cocoa butter equivalent (CBE) is added to Easter eggs. Samples with and without CBE were evaluated by a selected panel and fourteen attributes best describing similarities and differences between them, were defined. Terms definition, reference materials and a consensus ballot were developed. After a training period, panelists evaluated the samples in a Complete Block Design using a 9 cm unstructured scale. Principal Component Analysis, ANOVA and Tukey test (p<0.05) were applied to the data in order to select attributes which best discriminated and characterized the samples. Samples showed significant differences (p<0.05) in all attributes. Easter egg without CBE showed higher intensities (p<0.05) in relation to the following descriptors: brown color, characteristic aroma, cocoa mass aroma, cocoa butter aroma, characteristic flavor, cocoa mass flavor, hardness and brittleness.

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Descriptive terminology and sensory profile of three varieties of brazilian varietal white wines (cultivars Riesling, Gewürztraminer and Chardonnay) were developed by a methodology based on the Quantitative Descriptive Analysis (QDA). The sensory panel consensually defined the sensory descriptors, their respective reference materials and the descriptive evaluation ballot. Ten individuals were selected as judges based on their discrimination, reproducibility and individual consensus with the sensory panel. Twelve descriptors were generated showing similarities and differences among the wine samples. Each descriptor was evaluated using a nine-centimeters non-structured scale with the intensity terms anchored at its ends. The collected data were analysed by ANOVA, Tukey test and Principal Component Analysis (PCA). The results showed a great difference within the sensory profile of Riesling and Gewürztraminer wines, whereas Chardonnay wines showed a lesser variation. PCA separated samples into two groups: a first group formed by wines higher in sweetness and fruitty flavor and aroma; and a second group of wines higher in sourness, adstringency, bitterness, alcoholic and fermented flavors.