Skip to Main content Skip to Navigation
Journal articles

Plant identification: Man vs. Machine: LifeCLEF 2014 plant identification challenge

Abstract : 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 withexperienced botanists and clearly outperform beginners and inexperienced testsubjects. 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.
Complete list of metadatas

Cited literature [25 references]  Display  Hide  Download

https://hal.inria.fr/hal-01182778
Contributor : Alexis Joly <>
Submitted on : Tuesday, August 11, 2015 - 4:01:52 PM
Last modification on : Thursday, July 2, 2020 - 2:02:58 PM
Long-term archiving on: : Thursday, November 12, 2015 - 10:11:30 AM

File

MTAP_Man_vs_Machine.pdf
Files produced by the author(s)

Identifiers

Citation

Pierre Bonnet, Alexis Joly, Hervé Goëau, Julien Champ, Christel Vignau, et al.. Plant identification: Man vs. Machine: LifeCLEF 2014 plant identification challenge. Multimedia Tools and Applications, Springer Verlag, 2016, LifeCLEF 2014 plant identification challenge, 75 (3), pp.1647-1665. ⟨10.1007/s11042-015-2607-4⟩. ⟨hal-01182778⟩

Share

Metrics

Record views

1549

Files downloads

1432