178 citations · 404 across the 10 of their papers we have counts for
11 papers
Ensemble Learning techniques for object detection in high-resolution satellite images
Arthur Vilhelm, Matthieu Limbert, Clément Audebert +1
Ensembling is a method that aims to maximize the detection performance by fusing individual detectors. While rarely mentioned in deep-learning articles applied to remote sensing, e…
Case-based reasoning for rare events prediction on strategic sites
Vincent Vidal, Marie-Caroline Corbineau, Tugdual Ceillier
Satellite imagery is now widely used in the defense sector for monitoring locations of interest. Although the increasing amount of data enables pattern identification and therefore…
Improving performance of aircraft detection in satellite imagery while limiting the labelling effort: Hybrid active learning
Julie Imbert, Gohar Dashyan, Alex Goupilleau +2
The earth observation industry provides satellite imagery with high spatial resolution and short revisit time. To allow efficient operational employment of these images, automating…
Neural Architecture Search in operational context: a remote sensing case-study
Anthony Cazasnoves, Pierre-Antoine Ganaye, Kévin Sanchis +1
Deep learning has become in recent years a cornerstone tool fueling key innovations in the industry, such as autonomous driving. To attain good performances, the neural network arc…
Active learning for object detection in high-resolution satellite images
Alex Goupilleau, Tugdual Ceillier, Marie-Caroline Corbineau
In machine learning, the term active learning regroups techniques that aim at selecting the most useful data to label from a large pool of unlabelled examples. While supervised dee…
Concurrent Segmentation and Object Detection CNNs for Aircraft Detection and Identification in Satellite Images
Damien Grosgeorge, Maxime Arbelot, Alex Goupilleau +2
Detecting and identifying objects in satellite images is a very challenging task: objects of interest are often very small and features can be difficult to recognize even using ver…