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Segmentación de vasos sanguíneos en imágenes de resonancia magnética del cerebro
(2018-08-01)
RESUMEN:
En este trabajo se presenta la segmentación de venas, arterias y capilares (vasos
sanguíneos) en imágenes de resonancia magnética potenciadas por un líquido de
contraste en base a gadolinio. Las imágenes ...
K-means algorithm based on stochastic distances for polarimetric synthetic aperture radar image classification
(2016-10-01)
The availability of polarimetric synthetic aperture radar (PolSAR) images has increased, and consequently, the classification of such images has received immense attention. Among different classification methods in the ...
Parallelization of the Algorithm K-means Applied in Image Segmentation
(International Journal of Computer Applications, 2014-01-01)
Algorithm k-means is useful for grouping operations; however, when is applied to large amounts of data, its computational cost is high. This research propose an optimization of k-means algorithm by using parallelization ...
Uma análise do algoritmo K-means como introdução ao aprendizado de máquinas
(Universidade Federal do TocantinsAraguaínaCURSO::ARAGUAÍNA::PRESENCIALAraguaínaGraduação, 2020)
Mean Antarctic Circumpolar Current Transport Measured in Drake Passage
(American Geophysical Union, 2016-11)
The Antarctic Circumpolar Current is an important component of the global climate system connecting the major ocean basins as it flows eastward around Antarctica, yet due to the paucity of data it remains unclear how much ...
ALGORITMO K-MEANS PARALELO BASEADO EM HADOOP-MAPREDUCE PARA MINERAÇÃO DE DADOS AGRÍCOLAS
(UNIVERSIDADE ESTADUAL DE PONTA GROSSABRComputação para Tecnologias em AgriculturaPrograma de Pós Graduação Computação AplicadaUEPG, 2017)
ANÁLISE DE FUNÇÕES DE MEDIDA PARA O MÉTODO K-MEANS
(Florianópolis, SC, 2018)
A Hyperheuristic Approach for Unsupervised Land-Cover Classification
(Ieee-inst Electrical Electronics Engineers Inc, 2016-06-01)
Unsupervised land-use/cover classification is of great interest, since it becomes even more difficult to obtain high-quality labeled data. Still considered one of the most used clustering techniques, the well-known k-means ...