Classificação de imagens de sensoriamento remoto baseada em textura por redes neurais

O objetivo principal deste trabalho é propor uma metodologia de classificação de imagens de sensoriamento remoto que integre a importância de atributos de textura na seleção de feições, através da utilização de freqüências espaciais de cada classe textural e sua direção, com a eficiência das redes neurais artificiais para classificá-las. O processo é composto por uma etapa de filtragem baseada nos filtros de Gabor, seguida de uma fase de classificação através de uma rede neural Multi-Layer Perceptron com algoritmo BackPropagation. A partir da transformada de Fourier são estimados os parâmetros a serem utilizados na constituição dos filtros de Gabor, adequados às freqüências espaciais associadas a cada classe presente na imagem a ser classificada. Desta forma, cada filtro gera uma imagem filtrada. O conjunto de filtros determina um conjunto de imagens filtradas (canais texturais). A classificação pixel a pixel é realizada pela rede neural onde cada pixel é definido por um vetor de dimensionalidade igual ao número de filtros do conjunto. O processo de classificação através da rede neural Multi-Layer Perceptron foi realizado pelo método de classificação supervisionada. A metodologia de classificação de imagens de sensoriamento remoto proposta neste trabalho foi testada em imagens sintética e real de dimensões 256 x 256 pixels. A análise dos resultados obtidos é apresentada sob a forma de uma Matriz de Erros, juntamente com a discussão dos mesmos.

Detecção de fusos de sono em adultos jovens por meio de transformadas wavelet

A análise do sono está baseada na polissonogra a e o sinal de EEG é o mais importante. A necessidade de desenvolver uma análise automática do sono tem dois objetivos básicos: reduzir o tempo gasto na análise visual e explorar novas medidas quantitativas e suas relações com certos tipos de distúrbios do sono. A estrutura do sinal de EEG de sono está relacionada com a chamada microestrutura do sono, que é composta por grafoelementos. Um destes grafoelementos é o fuso de sono (spindles). Foi utilizado um delineamento transversal aplicado a um grupo de indivíduos normais do sexo masculino para testar o desempenho de um conjunto de ferramentas para a detecção automática de fusos. Exploramos a detecção destes fusos de sono através de procura direta, Matching Pursuit e uma rede neural que utiliza como "input"a transformada de Gabor (GT). Em comparação com a análise visual, o método utilizando a transformada de Gabor e redes neurais apresentou uma sensibilidade de 77% e especi cidade de 73%. Já o Matching Pursuit, apesar de mais demorado, se mostrou mais e ciente, apresentando sensibilidade de 81,2% e especi cidade de 85.2%.

Bandoniozyma gen. nov., a Genus of Fermentative and Non-Fermentative Tremellaceous Yeast Species

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

Oriented texture classification based on self-organizing neural network and Hough transform

This paper presents a technique for oriented texture classification which is based on the Hough transform and Kohonen's neural network model. In this technique, oriented texture features are extracted from the Hough space by means of two distinct strategies. While the first operates on a non-uniformly sampled Hough space, the second concentrates on the peaks produced in the Hough space. The described technique gives good results for the classification of oriented textures, a common phenomenon in nature underlying an important class of images. Experimental results are presented to demonstrate the performance of the new technique in comparison, with an implemented technique based on Gabor filters.

Loss of sleep spindle frequency deceleration in Obstructive Sleep Apnea

Objective: Sleep spindles have been suggested as surrogates of thalamo-cortical activity. Internal frequency modulation within a spindle's time frame has been demonstrated in healthy subjects, showing that spindles tend to decelerate their frequency before termination. We investigated internal frequency modulation of slow and fast spindles according to Obstructive Sleep Apnea (OSA) severity and brain topography. Methods: Seven non-OSA subjects and 21 patients with OSA contributed with 30 min of Non-REM sleep stage 2, subjected to a Matching pursuit procedure with Gabor chirplet functions for automatic detection of sleep spindles and quantification of sleep spindle internal frequency modulation (chirp rate). Results: Moderate OSA patients showed an inferior percentage of slow spindles with deceleration when compared to Mild and Non-OSA groups in frontal and parietal regions. In parietal regions, the percentage of slow spindles with deceleration was negatively correlated with global apnea-hypopnea index (r s = -0.519, p = 0.005). Discussion: Loss of physiological sleep spindle deceleration may either represent a disruption of thalamo-cortical loops generating spindle oscillations or some compensatory mechanism, an interesting venue for future research in the context of cognitive dysfunction in OSA. Significance: Quantification of internal frequency modulation (chirp rate) is proposed as a promising approach to advance description of sleep spindle dynamics in brain pathology. © 2013 International Federation of Clinical Neurophysiology.

Reconhecimento de pessoas por meio da região interna da íris

Pós-graduação em Ciência da Computação - IBILCE

Assessing signatures of selection through variation in linkage disequilibrium between taurine and indicine cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Classificação de tábuas de madeira usando processamento de imagens digitais e aprendizado de máquina

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Linkage disequilibrium levels in Bos indicus and Bos taurus cattle using medium and high density SNP chip data and different minor allele frequency distributions

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Atenção temporal e análise da interferência da característica do estímulo na percepção

Attention is a phenomenon that allows the selection of relevant stimuli in order to prioritize them and improve their processing. This modulation could occur in any step of the process: in an early stage or in a late stage, more precisely, in a perceptive or motor stage. However, even with a rich literature about attention in time, there are still some divergences about how this modulation occurs. A hypothesis about it says that temporal attention would only be able to prepare the motor system to respond. The perceptual modulation would only occur when the temporal expectation is in combination with another expectation of a property with neuronal receptive field. In this situation, the receptive field's pre-activation is the explanation of how temporal attention would be capable to modulate perceptual process. The crucial objective was to test this hypothesis. In other words, it was to verify if the feature expectation of a stimulus (Gabor orientation) and its temporal expectancy interferes in perception quality. Two experiments were made: the first one tested the voluntary temporal expectation, and the second one tested the automatic temporal expectation. Our data shows that both Feature-based Attention and Temporal Attention improve the process of perception. Temporal expectation effects just occur in situations of competitive environment. Hypothesis verification was not conclusive, because of methodological problems

Aplicação de sistemas imunológicos artificiais para biometria facial: Reconhecimento de identidade baseado nas características de padrões binários

Pós-graduação em Engenharia Elétrica - FEIS

Low levels of taurine introgression in the current Brazilian Nelore and Gir indicine cattle populations

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Shape Changes of Pt Nanoparticles Induced by Deposition on Mesoporous Silica

Polyvinylpyrollidone (PVP)-capped platinum nanoparticles (NPs) are found to change shape from spherical to flat when deposited on mesoporous silica substrates (SBA-15). Transmission electron microscopy (TEM), small-angle X-ray scattering (SAXS), and extended X-ray absorption fine structure (EXAFS) analyses are used in these studies. The SAXS results indicate that, after deposition, the 2 nm NPs have an average gyration radius 22% larger than in solution, while the EXAFS measurements indicate a decrease in first neighbor co-ordination number from 9.3 to 7.4. The deformation of these small capped NPs is attributed to interactions with the surface of the SBA-15 support, as evidenced by X-ray absorption near-edge structure (XANES).

Underlying Event measurements in pp collisions at root s=0.9 and 7 TeV with the ALICE experiment at the LHC

We present measurements of Underlying Event observables in pp collisions at root s = 0 : 9 and 7 TeV. The analysis is performed as a function of the highest charged-particle transverse momentum p(T),L-T in the event. Different regions are defined with respect to the azimuthal direction of the leading (highest transverse momentum) track: Toward, Transverse and Away. The Toward and Away regions collect the fragmentation products of the hardest partonic interaction. The Transverse region is expected to be most sensitive to the Underlying Event activity. The study is performed with charged particles above three different p(T) thresholds: 0.15, 0.5 and 1.0 GeV/c. In the Transverse region we observe an increase in the multiplicity of a factor 2-3 between the lower and higher collision energies, depending on the track p(T) threshold considered. Data are compared to PYTHIA 6.4, PYTHIA 8.1 and PHOJET. On average, all models considered underestimate the multiplicity and summed p(T) in the Transverse region by about 10-30%.

Water-assisted Flow of Heavy Oil in a Vertical Pipe: Pilot-scale Experiments

The use of the core-annular flow pattern, where a thin fluid surrounds a very viscous one, has been suggested as an attractive artificial-lift method for heavy oils in the current Brazilian ultra-deepwater production scenario. This paper reports the pressure drop measurements and the core-annular flow observed in a 2 7/8-inch and 300 meter deep pilot-scale well conveying a mixture of heavy crude oil (2000 mPa.s and 950 kg/m3 at 35 C) and water at several combinations of the individual flow rates. The two-phase pressure drop data are compared with those of single-phase oil flow to assess the gains due to water injection. Another issue is the handling of the core-annular flow once it has been established. High-frequency pressure-gradient signals were collected and a treatment based on the Gabor transform together with neural networks is proposed as a promising solution for monitoring and control. The preliminary results are encouraging. The pilot-scale tests, including long-term experiments, were conducted in order to investigate the applicability of using water to transport heavy oils in actual wells. It represents an important step towards the full scale application of the proposed artificial-lift technology. The registered improvements in terms of oil production rate and pressure drop reductions are remarkable.