34 citations · 74 across the 11 of their papers we have counts for
20 papers
Self-Configuring nnU-Nets Detect Clouds in Satellite Images
Bartosz Grabowski, Maciej Ziaja, Michal Kawulok +3
Cloud detection is a pivotal satellite image pre-processing step that can be performed both on the ground and on board a satellite to tag useful images. In the latter case, it can…
Self-supervised learning -- A way to minimize time and effort for precision agriculture?
Michael L. Marszalek, Bertrand Le Saux, Pierre-Philippe Mathieu +2
Machine learning, satellites or local sensors are key factors for a sustainable and resource-saving optimisation of agriculture and proved its values for the management of agricult…
Beyond Ansätze: Learning Quantum Circuits as Unitary Operators
Bálint Máté, Bertrand Le Saux, Maxwell Henderson
This paper explores the advantages of optimizing quantum circuits on wires as operators in the unitary group . We run gradient-based optimization in the Lie algebra $\m…
DIAL: Deep Interactive and Active Learning for Semantic Segmentation in Remote Sensing
Gaston Lenczner, Adrien Chan-Hon-Tong, Bertrand Le Saux +2
We propose in this article to build up a collaboration between a deep neural network and a human in the loop to swiftly obtain accurate segmentation maps of remote sensing images.…
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…
Pix2Point: Learning Outdoor 3D Using Sparse Point Clouds and Optimal Transport
Rémy Leroy, Pauline Trouvé-Peloux, Frédéric Champagnat +2
Good quality reconstruction and comprehension of a scene rely on 3D estimation methods. The 3D information was usually obtained from images by stereo-photogrammetry, but deep learn…