Fusion System Based on Belief Functions Theory and Approximated Belief Functions for Tree Species Recognition - Archive ouverte HAL Access content directly
Conference Papers Year : 2016

Fusion System Based on Belief Functions Theory and Approximated Belief Functions for Tree Species Recognition

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Abstract

In this paper, an information fusion system for tree species recognition through leaves is proposed. This approach consists in training sub-classifiers (Random forests) with attributes extracted from leaf photos. The database is incomplete, partial and some data is conflicting. A hierarchical fusion system based on Belief functions theory allows the fusion of data provided by different sub-classifiers. Different procedures for reducing computational complexity are tested.
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hal-01415621 , version 1 (13-12-2016)

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Rihab Ben Ameur, Lionel Valet, Didier Coquin. Fusion System Based on Belief Functions Theory and Approximated Belief Functions for Tree Species Recognition . IEEE International Conference on Image Processing Theory, Tools and Applications, Dec 2016, Oulu, Finland. 6 p., ⟨10.1109/IPTA.2016.7820955⟩. ⟨hal-01415621⟩
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