Guillaume Sicot

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In this paper, we propose a technique, based on a fuzzy Hidden Markov Chain (HMC) model, for the unsupervised seg-mentation of images. The main contribution of this work is to simultaneously use Dirac and Lebesgue measures at the class chain level. This model allows the coexistence of hard and fuzzy pixels in the same picture. In this way, the fuzzy(More)
In decentralized communication schemes such as ad-hoc networks, a major challenge concerns the synchronization and detection of users sending information simultaneously. Classical synchronisa-tion techniques based on training sequences decrease dramatically the spectral efficiency and are rarely applicable in non-cooperative settings. In this contribution,(More)
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