Integrate automatic identification tools customizable to your citizen science project needs: help your users identify the species from a picture.

Service description:

This service will develop an application that allows citizen science platforms (or other research projects) to develop automatic identification tools adapted to their needs, e.g. for particular groups of species. The identification tool, based on machine learning, will include a search to find similar results. For instance, among photographs of species that potentially resemble the observation made by the citizen scientist.

Example: A museum developing an app related to a particular group of species will be able to integrate a photo-identification tool for that species without much effort. 

Development & functioning :

The application will allow users to define a list of species of interest and, in return, the system will deploy a queryable contextualized identification web service through a secured web API and through a web GUI. Therefore, we will extend and improve the deep-learning-based similarity search engine already in use in the Pl@ntNet platform. This software allows users to identify observations composed of multiple part-based images of the same individual plant (e.g. leaf, flower, fruit, etc.), while returning the most similar observations in the database for each of the identified species, thanks to a scalable similarity-search engine that relies on high-dimensional data hashing and deep representations. 

Providing users with accurate visual feedback is crucial so they can control and (un)validate the proposed species.

Innovation for citizen observatories:

  • It will allow users to automatically identify species from a picture, based on artificial intelligence, and will return the most similar pictures in the database to control the proposed identification.
  • This technology will be refactored and extended so as to manage multiple tasks and models simultaneously and, in short, enables recognition of a much richer biodiversity (mammals, insects, etc.).
  • This application will be integrated as a new service in the DEEP-Hybrid-DataCloud marketplace

Questions & answers

  • Who is this service meant for? Do I need a technical background?

Developers or data scientists with a good background in data engineering and AI technologies.

  • Does AI-taxonomist only work with plants? Suppose I am a developer working on a citizen science project to monitor different bee species. Can I integrate this service to help my users with the identification?

Yes, AI-taxonomist works with both animals and plants, depending on your needs.

  • Does AI-taxonomist work with any official biodiversity databases to facilitate the similarity-search engine? Which ones?

By default, AI-taxonomist uses GBIF-DL to download images from GBIF. But you can make it work with any other image database.

We are working on this service, it will be available soon!


Deep learning, artificial intelligence, AI, species identification, DEEP-Hybrid-DataCloud.



Help us to co-create and test the new generation of services for citizen observatories!