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ICCV
2003
IEEE
16 years 8 months ago
Mean Shift Based Clustering in High Dimensions: A Texture Classification Example
Feature space analysis is the main module in many computer vision tasks. The most popular technique, k-means clustering, however, has two inherent limitations: the clusters are co...
Bogdan Georgescu, Ilan Shimshoni, Peter Meer
DAC
2006
ACM
16 years 7 months ago
A new hybrid FPGA with nanoscale clusters and CMOS routing
In this paper we propose a hybrid FPGA using nanoscale clusters with an architecture similar to clusters of traditional CMOS FPGAs. The proposed cluster is made of a crossbar of n...
Reza M. Rad, Mohammad Tehranipoor
ISBI
2008
IEEE
16 years 7 months ago
An information-based clustering approach for fMRI activation detection
Most clustering algorithms in fMRI analysis implicitly require some nontrivial assumption on data structure. Due to arbitrary distribution of fMRI time series in the temporal doma...
Lijun Bai, Wei Qin, Jimin Liang, Jie Tian
IPPS
1996
IEEE
15 years 11 months ago
Benefits of Processor Clustering in Designing Large Parallel Systems: When and How?
Advances in multiprocessor interconnect technologyare leading to high performance networks. However, software overheadsassociated with message passing are limiting the processors ...
Debashis Basak, Dhabaleswar K. Panda, Mohammad Ban...
PKDD
2000
Springer
107views Data Mining» more  PKDD 2000»
15 years 10 months ago
Expert Constrained Clustering: A Symbolic Approach
Abstract. A new constrained model is discussed as a way of incorporating efficiently a priori expert knowledge into a clustering problem of a given individual set. The first innova...
Fabrice Rossi, Frédérick Vautrain