733 citations · 2k across the 17 of their papers we have counts for
18 papers
SAGE: A sampling-aware global evaluation benchmark for species distribution modeling
Emilia Arens, Nina van Tiel, Robin Zbinden +8
Knowing where species occur is fundamental for biodiversity research and conservation. Species distribution models (SDMs) link species observations to environmental conditions to e…
MaskSDM with Shapley values to improve flexibility, robustness, and explainability in species distribution modeling
Robin Zbinden, Nina van Tiel, Gencer Sumbul +3
Species Distribution Models (SDMs) play a vital role in biodiversity research, conservation planning, and ecological niche modeling by predicting species distributions based on env…
Multi-Scale and Multimodal Species Distribution Modeling
Nina van Tiel, Robin Zbinden, Emanuele Dalsasso +3
Species distribution models (SDMs) aim to predict the distribution of species by relating occurrence data with environmental variables. Recent applications of deep learning to SDMs…
POLO -- Point-based, multi-class animal detection
Giacomo May, Emanuele Dalsasso, Benjamin Kellenberger +1
Automated wildlife surveys based on drone imagery and object detection technology are a powerful and increasingly popular tool in conservation biology. Most detectors require train…
On the selection and effectiveness of pseudo-absences for species distribution modeling with deep learning
Robin Zbinden, Nina van Tiel, Benjamin Kellenberger +2
Species distribution modeling is a highly versatile tool for understanding the intricate relationship between environmental conditions and species occurrences. However, the availab…
Teaching Computer Vision for Ecology
Elijah Cole, Suzanne Stathatos, Björn Lütjens +5
Computer vision can accelerate ecology research by automating the analysis of raw imagery from sensors like camera traps, drones, and satellites. However, computer vision is an eme…