Ruben Hagege

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We consider the problem of estimating the geometric deformation of an object, with respect to some reference observation on it. Existing solutions, set in the standard coordinate system imposed by the measurement system, lead to high-dimensional, non-convex optimization problems. In we proposed a novel framework that employs a set of non-linear functionals(More)
Coordinated studies with the SEM and CTEM have allowed the authors to observe in situ the morphology and ultrastructure of about twenty different types of hair selected on the basis of their different characteristics when studied by optical microscopy. The new data thus obtained make it possible to classify the different types of hairs in a logical order(More)
Many of the language identification (LID) systems are based on language models using machine learning (ML) techniques that take into account the fluctuation of speech over time, such as Hidden Markov Models (HMM). Considering the fluctuation of speech results LID systems use relatively long recording intervals to obtain reasonable accuracy. This research(More)
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