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Late Information Fusion for Multi-modality Plant Species Identification

Abstract : This article presents the participation of the ReVeS project to the ImageCLEF 2013 Plant Identification challenge. Our primary target being tree leaves, some extra effort had to be done this year to process images containing other plant organs. The proposed method tries to benefit from the presence of multiple sources of information for a same individual through the introduction of a late fusion system based on the decisions of classifiers for the different modalities. It also presents a way to incorporate the geographical information in the determination of the species by estimating their plausibility at the considered location. While maintaining its performance on leaf images (ranking 3rd on natural images and 4th on plain backgrounds) our team performed honorably on the brand new modalities with a 6th position.
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https://hal.archives-ouvertes.fr/hal-00872903
Contributor : Guillaume Cerutti <>
Submitted on : Monday, October 14, 2013 - 3:54:44 PM
Last modification on : Tuesday, June 1, 2021 - 2:08:07 PM
Long-term archiving on: : Friday, April 7, 2017 - 10:52:17 AM

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  • HAL Id : hal-00872903, version 1

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Guillaume Cerutti, Laure Tougne, Céline Sacca, Thierry Joliveau, Pierre-Olivier Mazagol, et al.. Late Information Fusion for Multi-modality Plant Species Identification. Conference and Labs of the Evaluation Forum, Sep 2013, Valencia, Spain. pp.Working Notes. ⟨hal-00872903⟩

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