no code implementations • 20 Dec 2023 • Anthony Kalaydjian, Anton Balykov, Alexi Semiz, Adrien Chan-Hon-Tong
Physical based simulations can be very time and computationally demanding tasks.
no code implementations • 12 Dec 2022 • Pol Labarbarie, Adrien Chan-Hon-Tong, Stéphane Herbin, Milad Leyli-Abadi
Although deep networks have shown vulnerability to evasion attacks, such attacks have usually unrealistic requirements.
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.
no code implementations • 29 Jan 2021 • Thomas Chaffre, Julien Moras, Adrien Chan-Hon-Tong, Julien Marzat, Karl Sammut, Gilles Le Chenadec, Benoit Clement
We compare it, in realistic simulations, to a model-free controller that uses the same deep reinforcement learning framework for the control of a micro aerial vehicle under wind gust.
no code implementations • 13 Nov 2020 • Guillaume Vaudaux-Ruth, Adrien Chan-Hon-Tong, Catherine Achard
Literature on self-assessment in machine learning mainly focuses on the production of well-calibrated algorithms through consensus frameworks i. e. calibration is seen as a problem.
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.
no code implementations • 30 Apr 2020 • Thomas Chaffre, Julien Moras, Adrien Chan-Hon-Tong, Julien Marzat
Transferring learning-based models to the real world remains one of the hardest problems in model-free control theory.
no code implementations • 15 Apr 2020 • Guillaume Vaudaux-Ruth, Adrien Chan-Hon-Tong, Catherine Achard
In this work, we propose to directly compute this ordered list by sparsely browsing the video and selecting one frame per action instance, task known as action spotting in literature.