3.2k citations · 11.3k across the 87 of their papers we have counts for
13 papers · 1 filter
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…
Multilingual Vision-Language Pre-training for the Remote Sensing Domain
João Daniel Silva, Joao Magalhaes, Devis Tuia +1
Methods based on Contrastive Language-Image Pre-training (CLIP) are nowadays extensively used in support of vision-and-language tasks involving remote sensing data, such as cross-m…
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…
Multi-Scale Grouped Prototypes for Interpretable Semantic Segmentation
Hugo Porta, Emanuele Dalsasso, Diego Marcos +1
Prototypical part learning is emerging as a promising approach for making semantic segmentation interpretable. The model selects real patches seen during training as prototypes and…
What to align in multimodal contrastive learning?
Benoit Dufumier, Javiera Castillo-Navarro, Devis Tuia +1
Humans perceive the world through multisensory integration, blending the information of different modalities to adapt their behavior. Contrastive learning offers an appealing solut…
Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants
Beatriz Borges, Negar Foroutan, Deniz Bayazit +87
AI assistants are being increasingly used by students enrolled in higher education institutions. While these tools provide opportunities for improved teaching and education, they a…
Knowledge-aware Text-Image Retrieval for Remote Sensing Images
Li Mi, Xianjie Dai, Javiera Castillo-Navarro +1
Image-based retrieval in large Earth observation archives is challenging because one needs to navigate across thousands of candidate matches only with the query image as a guide. B…
Cross-Modal Learning of Housing Quality in Amsterdam
Alex Levering, Diego Marcos, Devis Tuia
In our research we test data and models for the recognition of housing quality in the city of Amsterdam from ground-level and aerial imagery. For ground-level images we compare Goo…
Imbalance-aware Presence-only Loss Function for Species Distribution Modeling
Robin Zbinden, Nina van Tiel, Marc Rußwurm +1
In the face of significant biodiversity decline, species distribution models (SDMs) are essential for understanding the impact of climate change on species habitats by connecting e…
ConGeo: Robust Cross-view Geo-localization across Ground View Variations
Li Mi, Chang Xu, Javiera Castillo-Navarro +4
Cross-view geo-localization aims at localizing a ground-level query image by matching it to its corresponding geo-referenced aerial view. In real-world scenarios, the task requires…
ConVQG: Contrastive Visual Question Generation with Multimodal Guidance
Li Mi, Syrielle Montariol, Javiera Castillo-Navarro +3
Asking questions about visual environments is a crucial way for intelligent agents to understand rich multi-faceted scenes, raising the importance of Visual Question Generation (VQ…
Large Language Models for Captioning and Retrieving Remote Sensing Images
João Daniel Silva, João Magalhães, Devis Tuia +1
Image captioning and cross-modal retrieval are examples of tasks that involve the joint analysis of visual and linguistic information. In connection to remote sensing imagery, thes…
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…