« Semi-supervised Deep Learning for image sequences: Applications to autonomous driving and remote sensing »

In contrast, this paper presents remote sensing experiments (object de- tection and image segmentation on remote sensing datasets) which shows consistently that the offered

In our last experiment, we show that L γ - PageRank, adapted to the multi-class setting described in Section 2.3, can improve the performance of G-SSL in the presence of

Consider a safe state xκ at time tκ = κτ , a desired system control uκdes and assume that all new vehicles enter the supervision area safely with a margin τ.. Note that this

A typical scenario for apprenticeship learning is to have an expert performing a few optimal (or close to the optimal) trajectories and use these to learn a good policy.. In this

For example, when using only 5% of the image pixels for training, the 3D archi- tecture can’t overpass the 98% accuracy rate in the case of the Pavia University dataset (even when

In this work, we employ a transductive label propagation method that is based on the manifold assumption to make predictions on the entire dataset and use these predictions to

Dans cet article, nous proposons un réseau convolutionnel, associé à un mécanisme d’attention, permettant l’exploitation du signal audio brut, afin non seulement de classifier,

We proposed a method for interactive classification of remote sensing images consid- ering multiscale segmentation: the interactive HMSC (Hierarchical Multiscale Classifier)..