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Genome-wide analysis at the level of single cells has recently emerged as a powerful tool to dissect genome heterogeneity in cancer, neurobiology, and development. To be truly transformative, single-cell approaches must affordably accommodate large numbers of single cells. This is feasible in the case of copy number variation (CNV), because CNV(More)
In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear statistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective(More)
The ArosDyn project aims to develop an embedded software for robust analysis of dynamic scenes in urban environment during car driving. The software is based on Bayesian fusion of data from telemetric sensors (lidars) and visual sensors (stereo camera). The key objective is to process the dynamic scenes in real time to detect and track multiple moving(More)
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