Unsupervised Classification
Mostrando 1-12 de 22 artigos, teses e dissertações.
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1. Encoding of Luminescent Ink Markers Using Low-Level Data Fusion and Chemometrics
The identification and analysis of documentary fraud is always a challenge for forensic science. Document analysis has proven to be an important branch of forensics in elucidating the authenticity of documents. The development and incorporation of luminescent inks in authentic documents have proved to be an excellent security feature. This paper purposes the
Journal of the Brazilian Chemical Society. Publicado em: 2023
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2. Vibrational Spectroscopy and Chemometrics in Forensic Chemistry: Critical Review, Current Trends and Challenges
The present manuscript makes an extensive review of the scientific approaches developed in the last decade involving infrared and Raman spectroscopy combined with chemometrics for solving several issues in the investigation of the most relevant forensic traces, such as questioned documents and currency, explosives, gunshot residues, illicit drugs and body fl
J. Braz. Chem. Soc.. Publicado em: 24/10/2019
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3. Gene expression profile analysis of human intervertebral disc degeneration
In this study, we used microarray analysis to investigate the biogenesis and progression of intervertebral disc degeneration. The gene expression profiles of 37 disc tissue samples obtained from patients with herniated discs and degenerative disc disease collected by the National Cancer Institute Cooperative Tissue Network were analyzed. Differentially expre
Genet. Mol. Biol.. Publicado em: 2013
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4. GEOESTATÍSTICA E IMAGENS ORBITAIS PARA CARACTERIZAR A DISTRIBUIÇÃO ESPACIAL E DANOS DE LARVAS DE MELOLONTÍDEOS EM CEREAIS DE INVERNO / GEOSTATISTICS AND ORBITAL IMAGES FOR CHARACTERIZING THE SPATIAL DISTRIBUTION AND DAMAGES OF LARVAL MELOLONTÍDEOS IN WINTER CROPS
This study aimed to analyze the spatial distribution and use of orbital images for the identification of white grub damage. Will be presented in two chapters, the chapter one, presents the geostatistical characterization of white grub spatial distribution and chapter two describes the use of orbital images for the identification of white grub damage. Surveys
Publicado em: 2010
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5. Unsupervised methods of classifying remotely sensed imges using Kohonen self-organizing maps / Metodos de classificação não-supervisionada de imagens de sensoriamento remoto usando mapas auto-organizaveis de Kohonen
This thesis proposes new methods of unsupervised classification for remotely sensed images which particularly exploit the characteristics and properties of the Kohonen Self-Organizing Map (SOM). The key point is to execute the clustering process through a set of prototypes of SOM instead of analyzing directly the original patterns of the image. This strategy
Publicado em: 2009
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6. Evaluation of optimal and suboptimal feature selection methods applied to image textures / Avaliação de métodos ótimos e subótimos de seleção de características de texturas em imagens
Texture features are eficient image descriptors and can be employed in a wide range of applications, such as classification and segmentation. However, when the number of features is considerably high, pattern recognition tasks may be compromised. Feature selection helps prevent this problem, as it can be used to reduce data dimensionality and reveal features
Publicado em: 2008
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7. An ecoregional classification for the state of Roraima, Brazil: the importance of landscape in malaria biology
Understanding the different background landscapes in which malaria transmission occurs is fundamental to understanding malaria epidemiology and to designing effective local malaria control programs. Geology, geomorphology, vegetation, climate, land use, and anopheline distribution were used as a basis for an ecological classification of the state of Roraima,
Memórias do Instituto Oswaldo Cruz. Publicado em: 24/05/2007
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8. ClassificaÃÃo supervisionada usando dados simbÃlicos de semÃntica modal
The Symbolic Data Analysis (SDA) is a domain in the area of automatic discovery of knowledge that it aims at to develop methods for described data for variables that can assume as value lists of categories, intervals or distributions of probability. These variables allow to take in account the variability and/or uncertainty present in the data. This work pre
Publicado em: 2007
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9. Spatial analysis of plutonics bodies of mineiro belt trough integration of geological, airbone geophysical data and geochemical data / Analise espacial dos corpos plutonicos do cinturão mineiro atraves da integração de dados geologicos, aerogeofisicos e geoquimicos
Airborne geophysical data acquired over the Mineiro Belt in the southern portion of the São Francisco Craton, Minas Gerais, Brazil display patterns not previously identified by geological field mapping. The lack of rock exposures and connections among rock formations at surface poses problems for regional geologic mapping and interpretation, which are diffi
Publicado em: 2006
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10. Comparative analysis of clustering methods for gene expression time course data
This work performs a data driven comparative study of clustering methods used in the analysis of gene expression time courses (or time series). Five clustering methods found in the literature of gene expression analysis are compared: agglomerative hierarchical clustering, CLICK, dynamical clustering, k-means and self-organizing maps. In order to evaluate the
Genetics and Molecular Biology. Publicado em: 2004
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11. P-Band radar data classification by neural network for Amazonin land cover assessment / Uso de rede neural artificial não supervisionada na classificação de dados de radar na Banda-P para mapeamento de cobertura da terra em floresta tropical
The applicability of P-band radar data for land cover mapping using the unsupervised artificial neural network Fuzzy-ART (Adaptive Resonance Theory) is evaluated. The study area is located near Tapajós National Forest in the State of Para, Brazil. The radar data was acquired during an airborne mission conducted by AeroSensing RadarSystem GmbH in september 2
Publicado em: 2003
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12. Comparative analysis of clustering methods for gene expression data
Large scale approaches, namely proteomics and transcriptomics, will play the most important role of the so-called post-genomics. These approaches allow experiments to measure the expression of thousands of genes from a cell in distinct time points. The analysis of this data can allow the the understanding of gene function and gene regulatory networks (Eisen
Publicado em: 2003