1 citations · 1 across the 1 of their papers we have counts for
4 papers
BotaCLIP: Contrastive Learning for Botany-Aware Representation of Earth Observation Data
Selene Cerna, Sara Si-Moussi, Wilfried Thuiller +2
Foundation models have demonstrated a remarkable ability to learn rich, transferable representations across diverse modalities such as images, text, and audio. In modern machine le…
Uncovering symmetric and asymmetric species associations from community and environmental data
Sara Si-Moussi, Esther Galbrun, Mickael Hedde +3
There is no much doubt that biotic interactions shape community assembly and ultimately the spatial co-variations between species. There is a hope that the signal of these biotic i…
Continental-scale habitat distribution modelling with multimodal earth observation foundation models
Sara Si-Moussi, Stephan Hennekens, Sander Mucher +6
Habitats integrate the abiotic conditions, vegetation composition and structure that support biodiversity and sustain nature's contributions to people. Most habitats face mounting…
EUNIS Habitat Maps: Enhancing Thematic and Spatial Resolution for Europe through Machine Learning
Sara Si-Moussi, Stephan Hennekens, Sander Mücher +17
The EUNIS habitat classification is crucial for categorising European habitats, supporting European policy on nature conservation and implementing the Nature Restoration Law. To me…