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Plant identification: man vs. machine. LifeCLEF 2014 plant identification challenge

Bonnet P., Joly A., Goeau H., Champ J., Vignau C., Molino J.F., Barthélémy D., Boujemaa N.. 2016. Multimedia Tools and Applications, 75 (3) : p. 1647-1665.

This paper reports a large-scale experiment aimed at evaluating how state-of-art computer vision systems perform in identifying plants compared to human expertise. A subset of the evaluation dataset used within LifeCLEF 2014 plant identification challenge was therefore shared with volunteers of diverse expertise, ranging from the leading experts of the targeted flora to inexperienced test subjects. In total, 16 human runs were collected and evaluated comparatively to the 27 machine-based runs of LifeCLEF challenge. One of the main outcomes of the experiment is that machines are still far from outperforming the best expert botanists at the image-based plant identification competition. On the other side, the best machine runs are competing with experienced botanists and clearly outperform beginners and inexperienced test subjects. This shows that the performances of automated plant identification systems are very promising and may open the door to a new generation of ecological surveillance systems. (Résumé d'auteur)

Mots-clés : flore; plante; taxonomie; identification; banque de données; photographie; logiciel; analyse de données; méthode statistique

Thématique : Taxonomie végétale et phyto-géographie; Méthodes de relevé; Méthodes mathématiques et statistiques; Documentation et information

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