Nearest neighborhood consistency is an important concept in statistical pattern recognition, which underlies the well-known k-nearest neighbor method. In this paper, we combine th...
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...
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...
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...
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...