Sparse Representation
Mostrando 1-9 de 9 artigos, teses e dissertações.
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1. Rapid and Automatic Classification of Tobacco Leaves Using a Hand-Held DLP-Based NIR Spectroscopy Device
A hand-held near infrared (NIR) spectroscopy device is much more convenient than a traditional desktop NIR instrument. Thus, it is more suitable for the practical application. An automatic and rapid tool for grading tobacco leaves on the spot using a hand-held digital light processing (DLP)-based NIR spectroscopy device is proposed in this paper. Firstly, th
J. Braz. Chem. Soc.. Publicado em: 16/09/2019
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2. Automatic Identification of Cigarette Brand Using Near-Infrared Spectroscopy and Sparse Representation Classification Algorithm
A cigarette brand automatic classification method using near-infrared (NIR) spectroscopy and sparse representation classification (SRC) algorithm is put forward by the paper. Comparing with the traditional methods, it is more robust to redundancy because it uses non-negative least squares (NNLS) sparse coding instead of principal component analysis (PCA) for
J. Braz. Chem. Soc.. Publicado em: 2018-07
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3. Novel Image Classification technique using Particle Filter Framework optimised by Multikernel Sparse Representation
ABSTRACT The robustness and speed of image classification is still a challenging task in satellite image processing. This paper introduces a novel image classification technique that uses the particle filter framework (PFF)-based optimisation technique for satellite image classification. The framework uses a template-matching algorithm, comprising fast march
Braz. arch. biol. technol.. Publicado em: 23/01/2017
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4. Representação esparsa e modelo de esparsidade conjunta no reconhecimento de faces / Sparse Representation and Joint Sparsity Model in Face Recognition
O trabalho desenvolvido nesta dissertação propõe a utilização do modelo de esparsidade conjunta com complemento de matrizes (JSM-MC) para composição da base de treino no contexto de reconhecimento de faces utilizando o classificador baseado em representação esparsa (SRC). O método proposto visa trabalhar com imagens de faces em diferentes condiçõ
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 11/07/2012
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5. Estruturas de dados eficientes para algoritmos evolutivos aplicados a projeto de redes / Efficient Data Structures to Evolutionary Algorithms Applied to Network Design Problems.
Network design problems (NDPs) are very important since they involve several applications from areas of Engineering and Sciences. In order to solve the limitations of traditional algorithms for NDPs that involve real world complex networks (in general, modeled by large-scale complete or sparse graphs), heuristics, such as evolutionary algorithms (EAs), have
Publicado em: 2009
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6. Redução de ruído em sinais de voz usando curvas especializadas de modificação dos coeficientes da transformada em co-seno. / Speech denoising by softsoft thresholding.
Many noise-reduction methods are based on the possibility of representing the clean signal as a reduced number of coefficients of a block transform, so that cancelling coefficients below a certain thresholding level will produce an enhanced reconstructed signal. It is necessary to assume that the clean signal has a sparse representation, while the noise ener
Publicado em: 2006
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7. A inflexibilidade do espaço cartográfico, uma questão para a geografia: análise das discussões sobre o papel da cartografia / The inflexibility of space cartography, a matter for the geography: analysis of the discussions on the role of cartography
Is there a consensus that Cartography is the ideal language to express Geography? This is one of the key issues of our research. However, what might deserve an obvious affirmative answer, actually does not. Are we not living in a time when Cartography seems to be subtilized by Geography? Are we not losing this resource without putting up a struggle? On the o
Publicado em: 2004
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8. Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ1 minimization
Given a dictionary D = {dk} of vectors dk, we seek to represent a signal S as a linear combination S = ∑k γ(k)dk, with scalar coefficients γ(k). In particular, we aim for the sparsest representation possible. In general, this requires a combinatorial optimization process. Previous work considered the special case where D is an overcomplete system consist
National Academy of Sciences.
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9. Novel kingdom-level eukaryotic diversity in anoxic environments
Molecular evolutionary studies of eukaryotes have relied on a sparse collection of gene sequences that do not represent the full range of eukaryotic diversity in nature. Anaerobic microbes, particularly, have had little representation in phylogenetic studies. Such organisms are the least known of eukaryotes and probably are the most phylogenetically diverse.
The National Academy of Sciences.