: We propose an approach for quantifying the biological relatedness between gene products, based on their properties, and measure their similarities using exclusively statistical N...
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...
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...
: 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 ...
We address the problem of similarity metric selection in pairwise affinity clustering. Traditional techniques employ standard algebraic context-independent sample-distance measur...