output
20102026
most citedCurrent knowledge and future research opportunities for modeling annual crop mixtures. A review

130 citations

22 papers

q-bio.QM2026

A Comprehensive Database of Leaf Temperature, Water, and CO 2 Fluxes in Young Oil Palm Plants Across Diverse Climate Scenarios

Raphael Perez, Valentin Torrelli, Sandrine Roques +8

Functional-structural plant models (FSPM) replicate plants' responses to their environment and are useful for predicting behavior in a changing climate. However, they rely on detai…

cs.CV2025★ 50 cited

Overview of PlantCLEF 2021: cross-domain plant identification

Herve Goeau, Pierre Bonnet, Alexis Joly

Automated plant identification has improved considerably thanks to recent advances in deep learning and the availability of training data with more and more field photos. However,…

cs.CV2025★ 23 cited

Overview of PlantCLEF 2023: Image-based Plant Identification at Global Scale

Herve Goeau, Pierre Bonnet, Alexis Joly

The world is estimated to be home to over 300,000 species of vascular plants. In the face of the ongoing biodiversity crisis, expanding our understanding of these species is crucia…

stat.ML2025

Model-free algorithms for fast node clustering in SBM type graphs and application to social role inference in animals

Bertrand Cloez, Adrien Cotil, Jean-Baptiste Menassol +1

We propose a novel family of model-free algorithms for node clustering and parameter inference in graphs generated from the Stochastic Block Model (SBM), a fundamental framework in…

cs.CV2025★ 1 cited

Overview of PlantCLEF 2024: multi-species plant identification in vegetation plot images

Herve Goeau, Vincent Espitalier, Pierre Bonnet +1

Plot images are essential for ecological studies, enabling standardized sampling, biodiversity assessment, long-term monitoring and remote, large-scale surveys. Plot images are typ…

stat.CO2025★ 1 cited

Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation

Paul Bastide, Arnaud Estoup, Jean-Michel Marin +1

The marginal likelihood, or evidence, plays a central role in Bayesian model selection, yet remains notoriously challenging to compute in likelihood-free settings. While Simulation…