67 citations · 82 across the 2 of their papers we have counts for
5 papers
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…
Contextual Semantic Interpretability
Diego Marcos, Ruth Fong, Sylvain Lobry +3
Convolutional neural networks (CNN) are known to learn an image representation that captures concepts relevant to the task, but do so in an implicit way that hampers model interpre…
Semantically Interpretable Activation Maps: what-where-how explanations within CNNs
Diego Marcos, Sylvain Lobry, Devis Tuia
A main issue preventing the use of Convolutional Neural Networks (CNN) in end user applications is the low level of transparency in the decision process. Previous work on CNN inter…
Correcting rural building annotations in OpenStreetMap using convolutional neural networks
John E. Vargas-Muñoz, Sylvain Lobry, Alexandre X. Falcão +1
Rural building mapping is paramount to support demographic studies and plan actions in response to crisis that affect those areas. Rural building annotations exist in OpenStreetMap…
Scale equivariance in CNNs with vector fields
Diego Marcos, Benjamin Kellenberger, Sylvain Lobry +1
We study the effect of injecting local scale equivariance into Convolutional Neural Networks. This is done by applying each convolutional filter at multiple scales. The output is a…