LifeCLEF Plant Identification Task 2014
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866916975929720832 |
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| author | Goeau, Herve Joly, Alexis Bonnet, Pierre Selmi, Souheil Molino, Jean-Francois Barthelemy, Daniel Boujemaa, Nozha |
| author_facet | Goeau, Herve Joly, Alexis Bonnet, Pierre Selmi, Souheil Molino, Jean-Francois Barthelemy, Daniel Boujemaa, Nozha |
| contents | The LifeCLEFs plant identification task provides a testbed for a system-oriented evaluation of plant identification about 500 species trees and herbaceous plants. Seven types of image content are considered: scan and scan-like pictures of leaf, and 6 kinds of detailed views with unconstrained conditions, directly photographed on the plant: flower, fruit, stem & bark, branch, leaf and entire view. The main originality of this data is that it was specifically built through a citizen sciences initiative conducted by Tela Botanica, a French social network of amateur and expert botanists. This makes the task closer to the conditions of a real-world application. This overview presents more precisely the resources and assessments of task, summarizes the retrieval approaches employed by the participating groups, and provides an analysis of the main evaluation results. With a total of ten groups from six countries and with a total of twenty seven submitted runs, involving distinct and original methods, this fourth year task confirms Image & Multimedia Retrieval community interest for biodiversity and botany, and highlights further challenging studies in plant identification. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_23900 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | LifeCLEF Plant Identification Task 2014 Goeau, Herve Joly, Alexis Bonnet, Pierre Selmi, Souheil Molino, Jean-Francois Barthelemy, Daniel Boujemaa, Nozha Computer Vision and Pattern Recognition The LifeCLEFs plant identification task provides a testbed for a system-oriented evaluation of plant identification about 500 species trees and herbaceous plants. Seven types of image content are considered: scan and scan-like pictures of leaf, and 6 kinds of detailed views with unconstrained conditions, directly photographed on the plant: flower, fruit, stem & bark, branch, leaf and entire view. The main originality of this data is that it was specifically built through a citizen sciences initiative conducted by Tela Botanica, a French social network of amateur and expert botanists. This makes the task closer to the conditions of a real-world application. This overview presents more precisely the resources and assessments of task, summarizes the retrieval approaches employed by the participating groups, and provides an analysis of the main evaluation results. With a total of ten groups from six countries and with a total of twenty seven submitted runs, involving distinct and original methods, this fourth year task confirms Image & Multimedia Retrieval community interest for biodiversity and botany, and highlights further challenging studies in plant identification. |
| title | LifeCLEF Plant Identification Task 2014 |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2509.23900 |