Arsène Fansi Tchango

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This paper introduces the Voronoi diagram-based Artificial Immune System (VorAIS). VorAIS models the self/non-self using a Voronoi diagram that determines which areas of the problem domain correspond to self or to non-self. The diagram is evolved using a multi-objective bio-inspired approach in order to conjointly optimize various classification metrics(More)
This paper presents the Voronoi diagram-based evolutionary algorithm (VorEAl). VorEAl partitions input space in abnormal/normal subsets using Voronoi diagrams. Diagrams are evolved using a multi-objective bio-inspired approach in order to conjointly optimize classification metrics while also being able to represent areas of the data space that are not(More)
Tracking and understanding moving pedestrian behaviors is of major concern for a growing number of applications. This problem, known as difficult, is more complex when the considered environment is not fully under sensory coverage. Classical approaches either focus on location estimation or attempt to build the relationship between possible activities in(More)
—In this paper, we describe and evaluate an original Monte Carlo JPDAF for tracking interacting autonomous targets in a cluttered environment. The originality of the proposed algorithm consists in reducing the complexity of the prediction step by selecting and separately updating groups of targets in interaction. The complexity of the correction step is(More)
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