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SBCCI
2003
ACM
129views VLSI» more  SBCCI 2003»
15 years 9 months ago
Hyperspectral Images Clustering on Reconfigurable Hardware Using the K-Means Algorithm
Unsupervised clustering is a powerful technique for understanding multispectral and hyperspectral images, being k-means one of the most used iterative approaches. It is a simple th...
Abel Guilhermino S. Filho, Alejandro César ...
CCECE
2006
IEEE
15 years 10 months ago
Hardware Edge Detection using an Altera Stratix NIOS2 Development Kit
— Edge detection is a computer vision algorithm that is very processor intensive. It is possible to increase the speed of the algorithm by using hardware parallelism. This paper ...
Jay Kraut
MM
2005
ACM
215views Multimedia» more  MM 2005»
15 years 9 months ago
OpenVIDIA: parallel GPU computer vision
Graphics and vision are approximate inverses of each other: ordinarily Graphics Processing Units (GPUs) are used to convert “numbers into pictures” (i.e. computer graphics). I...
James Fung, Steve Mann
BMCBI
2010
139views more  BMCBI 2010»
15 years 4 months ago
A highly efficient multi-core algorithm for clustering extremely large datasets
Background: In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput t...
Johann M. Kraus, Hans A. Kestler
168
Voted
DEBS
2010
ACM
15 years 8 months ago
Evaluation of streaming aggregation on parallel hardware architectures
We present a case study parallelizing streaming aggregation on three different parallel hardware architectures. Aggregation is a performance-critical operation for data summarizat...
Scott Schneider, Henrique Andrade, Bugra Gedik, Ku...