Cooperative learning of Pl@ntNet's Artificial Intelligence algorithm: how does it work and how can we improve it?

no code implementations • 5 Jun 2024 • Tanguy Lefort, Antoine Affouard, Benjamin Charlier, Jean-Christophe Lombardo, Mathias Chouet, Hervé Goëau, Joseph Salmon, Pierre Bonnet, Alexis Joly

This strategy estimates user expertise as a trust score per user based on their ability to identify plant species from crowdsourced data.

Identify ambiguous tasks combining crowdsourced labels by weighting Areas Under the Margin

no code implementations • 30 Sep 2022 • Tanguy Lefort, Benjamin Charlier, Alexis Joly, Joseph Salmon

We adapt the AUM to identify ambiguous tasks in crowdsourced learning scenarios, introducing the Weighted Areas Under the Margin (WAUM).

Image Classification

Benchopt: Reproducible, efficient and collaborative optimization benchmarks

3 code implementations • 27 Jun 2022 • Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupré La Tour, Ghislain Durif, Cassio F. Dantas, Quentin Klopfenstein, Johan Larsson, En Lai, Tanguy Lefort, Benoit Malézieux, Badr Moufad, Binh T. Nguyen, Alain Rakotomamonjy, Zaccharie Ramzi, Joseph Salmon, Samuel Vaiter

Numerical validation is at the core of machine learning research as it allows to assess the actual impact of new methods, and to confirm the agreement between theory and practice.

Benchmarking Image Classification +1