1,720,976 research outputs found
Spectral band selection for ensemble classification of hyperspectral images with applications to agriculture and food safety
Get PDFIn this dissertation, an ensemble non-uniform spectral feature selection and a kernel density decision fusion framework are proposed for the classification of hyperspectral data using a support vector machine classifier. Hyperspectral data has more number of bands and they are always highly correlated. To utilize the complete potential, a feature selection step is necessary. In an ensemble situation, there are mainly two challenges: (1) Creating diverse set of classifiers in order to achieve a higher classification accuracy when compared to a single classifier. This can either be achieved by having different classifiers or by having different subsets of features for each classifier in the ensemble. (2) Designing a robust decision fusion stage to fully utilize the decision produced by individual classifiers. This dissertation tests the efficacy of the proposed approach to classify hyperspectral data from different applications. Since these datasets have a small number of training samples with larger number of highly correlated features, conventional feature selection approaches such as random feature selection cannot utilize the variability in the correlation level between bands to achieve diverse subsets for classification. In contrast, the approach proposed in this dissertation utilizes the variability in the correlation between bands by dividing the spectrum into groups and selecting bands from each group according to its size. The intelligent decision fusion proposed in this approach uses the probability density of training classes to produce a final class label. The experimental results demonstrate the validity of the proposed framework that results in improvements in the overall, user, and producer accuracies compared to other state-of-the-art techniques. The experiments demonstrate the ability of the proposed approach to produce more diverse feature selection over conventional approaches
Estudo comparativo de técnicas de análise de textura em imagens e aprendizagem de máquina para classificação de Phragmites australis usando imagens de alta resolução com cor no espectro do visível
Get PDFTCC(graduação) - Universidade Federal de Santa Catarina. Campus Araranguá. Engenharia da Computação.Phragmites australis (common reed) comumente encontrada em zonas úmidas costeiras pode alterar rapidamente a ecologia por competir e superar as plantas nativas por espaço e pelos recursos. Além disso, este tipo de vegetação representa um perigo de navegação para embarcações menores, prejudicando a visibilidade ao longo do litoral e em torno de curvas e canais de rios. Os esforços de gerencialmento direcionados a plantas não nativas de Phragmites dependem fortemente de um mapeamento preciso das áreas invadidads. No entanto, o mapeamento de Phragmites representa um desafio único por diferentes razões. Identificar e mapear Phragmites pode ajudar os gerentes de recurso a restaurar zonas húmidas afetadas. Neste trabalho, quatro técnicas de extração de características foram testadas: gabor filters, grey level co-occurrence matrix, segmentation-based fractal texture analysis e wavelet texture analysis. Estes algoritmos foram combinados com três estruturas de rede neural artificial: multilayer perceptron, probabilistic neural network e radial basis function network. Além disso, objetivando reduzir o tempo computacional, uma implementação na Graphics Processing Unit do melhor método identificado foi realizada. O estudo de avaliação foi realizado com imagens adquiridas no delta de Pearl River localizado no sudeste da Louisiana e no sudoeste do Mississippi, Estados Unidos da América. Em comparação com os resultados apresentados no estado da arte, wavelet texture analysis com probabilistic neural network e segmentation-based fractal texture analysis com probabilistic neural network apresentaram melhorias em várias variáveis estatísticas como acurácia geral e o kappa. Além disso, o nível de Phragmites agreement aumentou considerávelmente. Nos mostramos que os erros de omissão e comissão restantes geralmente estão localizados ao longo dos limites das áreas identificadas como Phragmites, o que reduz os esforços desnecessários para os gerentes de recursos na busca de áreas inexistentes.Phragmites australis (common reed) commonly found in the coastal wetlands can rapidly alter the ecology by outcompeting with natives for space and resources. In addition, this type of vegetation presents a navigation hazard to smaller boats by impairing visibility along shorelines and around bends of canals and rivers. Management efforts targeting non-native Phragmites rely heavily on accurately mapping invaded areas. However, mapping Phragmites represents a unique challenge for different reasons. Identifying and mapping Phragmites can help resource managers to restore affected wetlands. In this work, four feature extraction methods were tested: gabor filters, grey level co-occurrence matrix, segmentation-based fractal texture analysis, and wavelet texture analysis. These algorithms were combined with three artificial neural network architectures: multilayer perceptron, probabilistic neural network, and radial basis function network. In addition, aiming to reduce the computational cost, a graphics processing unit implementation of the best result was performed. Evaluation study was conducted with imagery acquired in the delta of Pearl River located in southeastern Louisiana and southwestern Mississippi, United States of America. In comparison to state-of-art results, wavelet texture analysis with probabilistic neural network and segmentation-based fractal texture analysis with probabilistic neural network presented presented improvements in several statistical variables such as overall accuracy and kappa value. Furthermore, the Phragmites agreement increased considerably. We show that the remaining omission and commission errors are generally located along boundaries of patches with Phragmites, which reduces unnecessary efforts for resource managers while searching for nonexistent patches
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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