Pl@ntNet automatically identified occurrences

Description :

 Pl@ntNet is a participatory botanical observation platform allowing to identify plants from photos (using deep learning) and to share the observations with the community. The platform has three main front-ends: Pl@ntNet androïd (http://bit.ly/1K4D1eU), Pl@ntNet iOS (http://apple.co/2cMtWgu) and Pl@ntNet web (https://identify.plantnet.org/). Pl@ntNet was founded in 2010 by a consortium of four French research organisms (CIRAD, Inria, INRAE and IRD) and is now open to other members. More information about Pl@ntNet can be found at https://plantnet.org/.  

The occurrences in this collection are Pl@ntNet observations that have been identified only by the deep learning algorithm but which the algorithm confidence was sufficiently high to consider them as valid.

Link GBIF portal : https://www.gbif.org/dataset/14d5676a-2c54-4f94-9023-1e8dcd822aa0

Project :
Title : Pl@ntNet Queries
Abstract : PlantNet is a participatory botanical observation platform allowing to identify plants from photos (using deep learning) and share observations with the community. This resource contains occurrences of plants automatically inferred from the plant observations submitted by the users of PlantNet application.
Funding : PlantNet is an open consortium founded by four French research organizations (CIRAD, Inria, INRAE, IRD) and supported by Agropolis Fondation. The two main funding resources are: (i) the annual contribution of the members of the consortium, (ii) donations from the end-users of PlantNet application (>10 million users).
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Publication dates :

First diffusion : 09/04/2021 

Last update : 22/04/2023