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SSPR
2004
Springer
15 years 9 months ago
Clustering Variable Length Sequences by Eigenvector Decomposition Using HMM
We present a novel clustering method using HMM parameter space and eigenvector decomposition. Unlike the existing methods, our algorithm can cluster both constant and variable leng...
Fatih Murat Porikli
CSB
2004
IEEE
123views Bioinformatics» more  CSB 2004»
15 years 8 months ago
A New Hardware Architecture for Genomic and Proteomic Sequence Alignment
We describe a novel hardware architecture for genomic and proteomic sequence alignment which achieves a speed-up of two to three orders of magnitude over Smith-Waterman dynamic pr...
Greg Knowles, Paul Gardner-Stephen
IJCV
2008
188views more  IJCV 2008»
15 years 4 months ago
Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods
The recent development of Sequential Monte Carlo methods (also called particle filters) has enabled the definition of efficient algorithms for tracking applications in image sequen...
Elise Arnaud, Étienne Mémin
CVPR
2010
IEEE
16 years 12 days ago
Sufficient Dimensionality Reduction for Visual Sequence Classification
When classifying high-dimensional sequence data, traditional methods (e.g., HMMs, CRFs) may require large amounts of training data to avoid overfitting. In such cases dimensional...
Alex Shyr, Raquel Urtasun, Michael Jordan
ICC
2009
IEEE
107views Communications» more  ICC 2009»
15 years 11 months ago
EM-Based Maximum-Likelihood Sequence Detection for MIMO Optical Wireless Systems
—A major performance-limiting factor in terrestrial optical wireless (OW) systems is turbulence-induced fading. Exploiting the additional degrees of freedom in the spatial dimens...
Nestor D. Chatzidiamantis, Murat Uysal, Theodoros ...