LifeCLEF: tackle machine learning challenges to help boost biodiversity in data science research!

LifeCLEF is a yearly event aimed at boosting research in biodiversity data science through machine learning-oriented challenges. The competition is opened to any interested research team, developer, student, etc.

Specifically, the 2021 edition of LifeCLEF includes four challenges:

  1. PlantCLEF: cross-domain plant identification based on herbarium sheets,
  2. BirdCLEF: bird species recognition in audio soundscapes.
  3. GeoLifeCLEF: location-based prediction of species based on environmental and occurrence data.
  4. SnakeCLEF: image-based snake identification.

What are the main objectives?

Each participant will develop their own method/algorithm to solve the targeted task. Once ready, the organizers will conduct a comparative study of the developed methods thanks to a standard evaluation dataset; this way, participants will evaluate their technology by comparing it to the state-of-the-art. 

The challenges’ results will be published in technical reports and scientific articles and presented at the Conference on Computer Vision and Pattern Recognition (CVPR), among other things.

Registration information


LifeCLEF 2021 organizers are: Pl@ntNetCos4CloudUniversité de GenèveCornell TechInriaTechnische Universität ChemnitzUniversité Monpellier and CNRS (The French National Centre for Scientific Research) and the Faculty of Applied Sciences of the University of West Bohemia