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Deep Learning and Earth Observation to Support the Sustainable Development Goals
Claudio Persello, Jan Dirk Wegner, Ronny Hänsch +4
The synergistic combination of deep learning models and Earth observation promises significant advances to support the sustainable development goals (SDGs). New developments and a…
Seeing biodiversity: perspectives in machine learning for wildlife conservation
Devis Tuia, Benjamin Kellenberger, Sara Beery +15
Data acquisition in animal ecology is rapidly accelerating due to inexpensive and accessible sensors such as smartphones, drones, satellites, audio recorders and bio-logging device…
How to find a good image-text embedding for remote sensing visual question answering?
Christel Chappuis, Sylvain Lobry, Benjamin Kellenberger +2
Visual question answering (VQA) has recently been introduced to remote sensing to make information extraction from overhead imagery more accessible to everyone. VQA considers a que…
Self-Supervised Pretraining and Controlled Augmentation Improve Rare Wildlife Recognition in UAV Images
Xiaochen Zheng, Benjamin Kellenberger, Rui Gong +2
Automated animal censuses with aerial imagery are a vital ingredient towards wildlife conservation. Recent models are generally based on deep learning and thus require vast amounts…
Mapping Vulnerable Populations with AI
Benjamin Kellenberger, John E. Vargas-Muñoz, Devis Tuia +6
Humanitarian actions require accurate information to efficiently delegate support operations. Such information can be maps of building footprints, building functions, and populatio…
Semisupervised Manifold Alignment of Multimodal Remote Sensing Images
Devis Tuia, Michele Volpi, Maxime Trolliet +1
We introduce a method for manifold alignment of different modalities (or domains) of remote sensing images. The problem is recurrent when a set of multitemporal, multisource, multi…