Many important problems involve clustering large datasets. Although naive implementations of clustering are computationally expensive, there are established efficient techniques f...
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Abstract—The application of neural networks (NN’s) to automatic analysis of chromosome images is investigated in this paper. All aspects of the analysis, namely segmentation, f...
Natural scene images brought new challenges for a few years and one of them is text understanding over images or videos. Text extraction which consists to segment textual foregrou...
Subspace clustering and frequent itemset mining via “stepby-step” algorithms that search the subspace/pattern lattice in a top-down or bottom-up fashion do not scale to large ...