4 citations · 12 across the 11 of their papers we have counts for
11 papers
How to Optimize Multispecies Set Predictions in Presence-Absence Modeling ?
Sébastien Gigot--Léandri, Gaétan Morand, Alexis Joly +4
Species distribution models (SDMs) commonly produce probabilistic occurrence predictions that must be converted into binary presence-absence maps for ecological inference and conse…
GeoPl@ntNet: A Platform for Exploring Essential Biodiversity Variables
Lukas Picek, César Leblanc, Alexis Joly +3
This paper describes GeoPl@ntNet, an interactive web application designed to make Essential Biodiversity Variables accessible and understandable to everyone through dynamic maps an…
Overview of PlantCLEF 2025: Multi-Species Plant Identification in Vegetation Quadrat Images
Giulio Martellucci, Herve Goeau, Pierre Bonnet +2
Quadrat images are essential for ecological studies, as they enable standardized sampling, the assessment of plant biodiversity, long-term monitoring, and large-scale field campaig…
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…
Mapping biodiversity at very-high resolution in Europe
César Leblanc, Lukas Picek, Benjamin Deneu +4
This paper describes a cascading multimodal pipeline for high-resolution biodiversity mapping across Europe, integrating species distribution modeling, biodiversity indicators, and…
Applying the maximum entropy principle to neural networks enhances multi-species distribution models
Maxime Ryckewaert, Diego Marcos, Christophe Botella +3
The rapid expansion of citizen science initiatives has led to a significant growth of biodiversity databases, and particularly presence-only (PO) observations. PO data are invaluab…
MALPOLON: A Framework for Deep Species Distribution Modeling
Theo Larcher, Lukas Picek, Benjamin Deneu +3
This paper describes a deep-SDM framework, MALPOLON. Written in Python and built upon the PyTorch library, this framework aims to facilitate training and inferences of deep species…
Fully automatic extraction of morphological traits from the Web: utopia or reality?
Diego Marcos, Robert van de Vlasakker, Ioannis N. Athanasiadis +7
Plant morphological traits, their observable characteristics, are fundamental to understand the role played by each species within their ecosystem. However, compiling trait informa…
GeoPlant: Spatial Plant Species Prediction Dataset
Lukas Picek, Christophe Botella, Maximilien Servajean +7
The difficulty of monitoring biodiversity at fine scales and over large areas limits ecological knowledge and conservation efforts. To fill this gap, Species Distribution Models (S…
Modelling Species Distributions with Deep Learning to Predict Plant Extinction Risk and Assess Climate Change Impacts
Joaquim Estopinan, Pierre Bonnet, Maximilien Servajean +2
The post-2020 global biodiversity framework needs ambitious, research-based targets. Estimating the accelerated extinction risk due to climate change is critical. The International…
AI-based Mapping of the Conservation Status of Orchid Assemblages at Global Scale
Joaquim Estopinan, Maximilien Servajean, Pierre Bonnet +2
Although increasing threats on biodiversity are now widely recognised, there are no accurate global maps showing whether and where species assemblages are at risk. We hereby assess…