Abstract. We present an approach based on clustering to segment renal arteries from 2D PC Cine MR images to measure blood velocity and flow. Such information are important in gradi...
: Temporal data mining is concerned with the analysis of temporal data and finding temporal patterns, regularities, trends, clusters in sets of temporal data. Wavelet transform pro...
The generation of a set of rules underlying a classification problem is performed by applying a new algorithm, called Hamming Clustering (HC). It reconstructs the and-or expressio...
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 ...