no code implementations • 28 Mar 2024 • Mamadou Dia, Ghazaleh Khodabandelou, Alice Othmani
Our proposed approach achieves state-of-the-art performances with an RMSE of 2. 92 on the eDAIC dataset thanks to the stochastic depth, stochastic deep learning layers, and stochastic activation function.
no code implementations • 11 Nov 2020 • Elnaz Soleimani, Ghazaleh Khodabandelou, Abdelghani Chibani, Yacine Amirat
The performance of Human Activity Recognition (HAR) models, particularly deep neural networks, is highly contingent upon the availability of the massive amount of annotated training data which should be sufficiently labeled.
1 code implementation • 4 Oct 2019 • Florent Chiaroni, Ghazaleh Khodabandelou, Mohamed-Cherif Rahal, Nicolas Hueber, Frederic Dufaux
In this manner, the discriminator is constrained to request the generator to converge towards the unlabeled samples distribution while diverging from the positive samples distribution.