Hicham Laanaya

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Each year, numerous segmentation and classification algorithms are invented or reused to solve problems where machine vision is needed. Generally, the efficiency of these algorithms is compared against the results given by one or many human experts. However, in many situations, the location of the real boundaries of the object as well as their classes are(More)
Caused by many applications during the last few years, many models have been proposed to represent imprecise and uncertain data. These models are essentially based on the theory of the theory of fuzzy sets, the theory of possibilities and the theory of belief functions. These two first theories are based on the membership functions and the last one on the(More)
– In this paper 1 , we present an approach of automatic seabed recognition from multiple views of side-scan sonar. We integrate detailed knowledge about each view: the nature of the seabed, the position and the uncertainty and the imprecision related to each information. To exploit information from multiple views, a fusion strategy for seabed recognition(More)
Keywords: Kernel optimization Support vector machines General Gaussian kernel Symmetric positive-definite matrices manifold a b s t r a c t We propose a new method for general Gaussian kernel hyperparameter optimization for support vector machines classification. The hyperparameters are constrained to lie on a differentiable manifold. The proposed(More)
—In this paper, we present various approaches for combining classifiers to improve classification of textured images, which are not generally used in this application framework. This is what we call post-classification step of textured images. Three approaches to combine classifiers are presented: the majority voting approach, belief approach, and(More)
La classification des images sonar est d'une grande importance par exemple pour la navigation sous-marine ou pour la cartographie des fonds ma-rins. En effet, le sonar offre des capacités d'imagerie plus performantes que les capteurs optiques en milieu sous-marin. La classification de ce type de données rencontre plusieurs difficultés en raison des(More)
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