François Munoz

According to our database, François Munoz authored at least 8 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Mapping global orchid assemblages with deep learning provides novel conservation insights.

Joaquim Estopinan, Maximilien Servajean, Pierre Bonnet, Alexis Joly, François Munoz

Ecol. Informatics, 2024

Modelling Species Distributions with Deep Learning to Predict Plant Extinction Risk and Assess Climate Change Impacts.

Joaquim Estopinan, Pierre Bonnet, Maximilien Servajean, François Munoz, Alexis Joly

CoRR, 2024

AI-based Mapping of the Conservation Status of Orchid Assemblages at Global Scale.

Joaquim Estopinan, Maximilien Servajean, Pierre Bonnet, Alexis Joly, François Munoz

CoRR, 2024

2021

Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment.

Benjamin Deneu, Maximilien Servajean, Pierre Bonnet, Christophe Botella, François Munoz, Alexis Joly

PLoS Comput. Biol., 2021

2020

How Do Deep Convolutional SDM Trained on Satellite Images Unravel Vegetation Ecology?

Benjamin Deneu, Alexis Joly, Pierre Bonnet, Maximilien Servajean, François Munoz

Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

Participation of LIRMM / Inria to the GeoLifeCLEF 2020 Challenge.

Benjamin Deneu, Maximilien Servajean, Pierre Bonnet, François Munoz, Alexis Joly

Proceedings of the Working Notes of CLEF 2020, 2020

2018

Overview of GeoLifeCLEF 2018: Location-based Species Recommendation.

Christophe Botella, Pierre Bonnet, François Munoz, Pascal Monestiez, Alexis Joly

Proceedings of the Working Notes of CLEF 2018, 2018

A Deep Learning Approach to Species Distribution Modelling.

Christophe Botella, Alexis Joly, Pierre Bonnet, Pascal Monestiez, François Munoz

Proceedings of the Multimedia Tools and Applications for Environmental & Biodiversity Informatics, 2018