5 citations · 7 across the 2 of their papers we have counts for
2 papers
cs.CV2022★ 2 cited
Self-Supervised Pretraining on Satellite Imagery: a Case Study on Label-Efficient Vehicle Detection
Jules BOURCIER, Thomas Floquet, Gohar Dashyan +3
In defense-related remote sensing applications, such as vehicle detection on satellite imagery, supervised learning requires a huge number of labeled examples to reach operational…
eess.IV2022★ 5 cited
Evaluating the Label Efficiency of Contrastive Self-Supervised Learning for Multi-Resolution Satellite Imagery
Jules Bourcier, Gohar Dashyan, Jocelyn Chanussot +1
The application of deep neural networks to remote sensing imagery is often constrained by the lack of ground-truth annotations. Adressing this issue requires models that generalize…