5 citations · 8 across the 2 of their papers we have counts for
3 papers
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.…
Interactive Learning for Semantic Segmentation in Earth Observation
Gaston Lenczner, Adrien Chan-Hon-Tong, Nicola Luminari +2
Dense pixel-wise classification maps output by deep neural networks are of extreme importance for scene understanding. However, these maps are often partially inaccurate due to a v…
DISIR: Deep Image Segmentation with Interactive Refinement
Gaston Lenczner, Bertrand Le Saux, Nicola Luminari +2
This paper presents an interactive approach for multi-class segmentation of aerial images. Precisely, it is based on a deep neural network which exploits both RGB images and annota…