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IJDMB
2008
117views more  IJDMB 2008»
15 years 5 months ago
Scoring and summarising gene product clusters using the Gene Ontology
: We propose an approach for quantifying the biological relatedness between gene products, based on their properties, and measure their similarities using exclusively statistical N...
Spiridon C. Denaxas, Christos Tjortjis
ICIP
2010
IEEE
15 years 2 months ago
Edge-adaptive image segmentation based on seam processing and K-Means clustering
A new image segmentation method is proposed to combine the edge information with the feature-space method, K-Means clustering. A procedure called seam processing, which is computa...
Tse-Wei Chen, Hsiao-Hang Su, Yi-Ling Chen, Shao-Yi...
TVLSI
2010
14 years 11 months ago
Bandwidth Adaptive Hardware Architecture of K-Means Clustering for Video Analysis
K-Means is a clustering algorithm that is widely applied in many fields, including pattern classification and multimedia analysis. Due to real-time requirements and computational-c...
Tse-Wei Chen, Shao-Yi Chien
ICCD
2003
IEEE
145views Hardware» more  ICCD 2003»
16 years 1 months ago
Care Bit Density and Test Cube Clusters: Multi-Level Compression Opportunities
: Most of the recently discussed and commercially introduced test stimulus data compression techniques are based on low care bit densities found in typical scan test vectors. Data ...
Bernd Könemann
ICASSP
2008
IEEE
15 years 11 months ago
Density geodesics for similarity clustering
We address the problem of similarity metric selection in pairwise affinity clustering. Traditional techniques employ standard algebraic context-independent sample-distance measur...
Umut Ozertem, Deniz Erdogmus, Miguel Á. Car...