2 citations · 6 across the 11 of their papers we have counts for
11 papers
Self-Supervised Learning of Plant Image Representations
Ilyass Moummad, Kawtar Zaher, Hervé Goëau +3
Automated plant recognition plays a crucial role in biodiversity monitoring and conservation, yet current approaches rely heavily on supervised learning, which is limited by the av…
Energy-Efficient Plant Monitoring via Knowledge Distillation
Ilyass Moummad, Reda Bensaid, Kawtar Zaher +5
Recent advances in large-scale visual representation learning have significantly improved performance in plant species and plant disease recognition tasks. However, state-of-the-ar…
Compact Hypercube Embeddings for Fast Text-based Wildlife Observation Retrieval
Ilyass Moummad, Marius Miron, David Robinson +7
Large-scale biodiversity monitoring platforms increasingly rely on multimodal wildlife observations. While recent foundation models enable rich semantic representations across visi…
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…
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…
Cooperative learning of Pl@ntNet's Artificial Intelligence algorithm: how does it work and how can we improve it?
Tanguy Lefort, Antoine Affouard, Benjamin Charlier +6
Deep learning models for plant species identification rely on large annotated datasets. The PlantNet system enables global data collection by allowing users to upload and annotate…