1 code implementation • 4 Jan 2022 • Gaston Lenczner, Adrien Chan-Hon-Tong, Bertrand Le Saux, Nicola Luminari, Guy Le Besnerais
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.
1 code implementation • 4 Jan 2022 • Gaston Lenczner, Adrien Chan-Hon-Tong, Nicola Luminari, Bertrand Le Saux
Transfer learning is a powerful way to adapt existing deep learning models to new emerging use-cases in remote sensing.
no code implementations • 28 May 2021 • Adrien Chan-Hon-Tong, Gaston Lenczner, Aurelien Plyer
Convolutional neural networks are currently the state-of-the-art algorithms for many remote sensing applications such as semantic segmentation or object detection.
1 code implementation • 23 Sep 2020 • Gaston Lenczner, Adrien Chan-Hon-Tong, Nicola Luminari, Bertrand Le Saux, Guy Le Besnerais
Dense pixel-wise classification maps output by deep neural networks are of extreme importance for scene understanding.
1 code implementation • 31 Mar 2020 • Gaston Lenczner, Bertrand Le Saux, Nicola Luminari, Adrien Chan Hon Tong, Guy Le Besnerais
Starting from an initial output based on the image only, our network then interactively refines this segmentation map using a concatenation of the image and user annotations.