901 resultados para Subfractals, Subfractal Coding, Model Analysis, Digital Imaging, Pattern Recognition


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This paper introduces the Optimum-Path Forest (OPF) classifier for static video summarization, being its results comparable to the ones obtained by some state-of-the-art video summarization techniques. The experimental section has been conducted using several image descriptors in two public datasets, followed by an analysis of OPF robustness regarding one ad-hoc parameter. Future works are guided to improve OPF effectiveness on each distinct video category.

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Prostate cancer is a serious public health problem accounting for up to 30% of clinical tumors in men. The diagnosis of this disease is made with clinical, laboratorial and radiological exams, which may indicate the need for transrectal biopsy. Prostate biopsies are discerningly evaluated by pathologists in an attempt to determine the most appropriate conduct. This paper presents a set of techniques for identifying and quantifying regions of interest in prostatic images. Analyses were performed using multi-scale lacunarity and distinct classification methods: decision tree, support vector machine and polynomial classifier. The performance evaluation measures were based on area under the receiver operating characteristic curve (AUC). The most appropriate region for distinguishing the different tissues (normal, hyperplastic and neoplasic) was defined: the corresponding lacunarity values and a rule's model were obtained considering combinations commonly explored by specialists in clinical practice. The best discriminative values (AUC) were 0.906, 0.891 and 0.859 between neoplasic versus normal, neoplasic versus hyperplastic and hyperplastic versus normal groups, respectively. The proposed protocol offers the advantage of making the findings comprehensible to pathologists. (C) 2014 Elsevier Ltd. All rights reserved.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Since the beginning, some pattern recognition techniques have faced the problem of high computational burden for dataset learning. Among the most widely used techniques, we may highlight Support Vector Machines (SVM), which have obtained very promising results for data classification. However, this classifier requires an expensive training phase, which is dominated by a parameter optimization that aims to make SVM less prone to errors over the training set. In this paper, we model the problem of finding such parameters as a metaheuristic-based optimization task, which is performed through Harmony Search (HS) and some of its variants. The experimental results have showen the robustness of HS-based approaches for such task in comparison against with an exhaustive (grid) search, and also a Particle Swarm Optimization-based implementation.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This paper introduces a new tool for pattern recognition. Called the Discriminative Paraconsistent Machine (DPM), it is based on a supervised discriminative model training that incorporates paraconsistency criteria and allows an intelligent treatment of contradictions and uncertainties. DPMs can be applied to solve problems in many fields of science, using the tests and discussions presented here, which demonstrate their efficacy and usefulness. Major difficulties and challenges that were overcome consisted basically in establishing the proper model with which to represent the concept of paraconsistency.

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The aim of this study was to evaluate the correlation of color change on bleaching tooth through delta E (ΔE) by the spectrophotometer Spectroshade (SS) and digital program Scanwhite (SW). Methods: 25 patient volunteers were recruited from Operative Dentistry at Universidad de Chile Dental School, between 18 to 30 years, with good oral hygiene. Exclusion criteria: Previous experienced tooth bleaching, anterior restorations, cervical lesions, pain dental, pregnant patient, stained teeth, malposition of the teeth and periodontal pathology. The bleaching was made in two sessions with three different bleaching systems which were randomly. The assessment of color change through ΔE was made on the two upper central incisors (N=50) by the SS and SW. The color in the same teeth were measured before (T0) and after (T1) of the bleaching treatment. Data were analyzed using test Spearman correlation coefficient (Rho) with a significant level of 95%. Results: The results showed a positive and significant correlation (0.676), with a statistically significant difference (p<0.05). Conclusion: There is correlation in the measurement of color change on bleaching tooth by SS and SW.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Photodynamic therapy (PDT) is used for skin treatments of premalignant and cancer lesions and recognized as a non-invasive technique that combines tissue photosensitization and subsequent exposure to light to induce cell death. However, it is limited to the treatment of superficial lesions, mainly due to the low cream penetration. Therefore, the improvement of transdermal distribution of aminolevulinic acid (ALA) is needed. In this study, the kinetics and homogeneity of production of ALA-induced PpIX after the skin pre-treatment with microneedles rollers of 0.5, 1.0 and 1.5 mm length were investigated. An improvement in homogeneity and production of PpIX was shown in a porcine model. Widefield fluorescence imaging three hours after the topical application of ALA-cream in the combined treatment with microeedles rollers.

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Pós-graduação em Engenharia Elétrica - FEIS

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)