activity
20192026
most citedEvaluation of Deep Species Distribution Models using Environment and Co-occurrences

7 citations · 12 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2026

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…

cs.CV2025

Overview of GeoLifeCLEF 2023: Species Composition Prediction with High Spatial Resolution at Continental Scale Using Remote Sensing

Christophe Botella, Benjamin Deneu, Diego Marcos +6

Understanding the spatio-temporal distribution of species is a cornerstone of ecology and conservation. By pairing species observations with geographic and environmental predictors…

cs.LG2024

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…

cs.CV2024

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…

q-bio.PE2023★ 3 cited

The GeoLifeCLEF 2023 Dataset to evaluate plant species distribution models at high spatial resolution across Europe

Christophe Botella, Benjamin Deneu, Diego Marcos +6

The difficulty to measure or predict species community composition at fine spatio-temporal resolution and over large spatial scales severely hampers our ability to understand speci…

cs.CV2020★ 2 cited

The GeoLifeCLEF 2020 Dataset

Elijah Cole, Benjamin Deneu, Titouan Lorieul +6

Understanding the geographic distribution of species is a key concern in conservation. By pairing species occurrences with environmental features, researchers can model the relatio…

cs.NE2019★ 7 cited

Evaluation of Deep Species Distribution Models using Environment and Co-occurrences

Benjamin Deneu, Maximilien Servajean, Christophe Botella +1

This paper presents an evaluation of several approaches of plants species distribution modeling based on spatial, environmental and co-occurrences data using machine learning metho…