Search results for "séries temporelles"
showing 4 items of 4 documents
Exploiting deep learning algorithms and satellite image time series for deforestation prediction
2022
In recent years, we have witnessed the emergence of Deep Learning (DL) methods, which have led to enormous progress in various fields such as automotive driving, computer vision, medicine, finances, and remote sensing data analysis. The success of these machine learning methods is due to the ever-increasing availability of large amounts of information and the computational power of computers. In the field of remote sensing, we now have considerable volumes of satellite images thanks to the large number of Earth Observation (EO) satellites orbiting the planet. With the revisit time of satellites over an area becoming shorter and shorter, it will probably soon be possible to obtain daily imag…
Théorie de système et séries temporelles
1994
The aim of this paper is to present a different representation of state space models, (innovation state space representation) which is relatively new and apparently unknown in the economics and econometrics literature and to describe some of its properties. state space representation is a very flexible form for time series and the approach taken in this paper therefore allows a broad class of models it does not impose a priori the decomposition of data series into trend and cycle
L'utilisation des données de télédétection et des méthodes de deep learning pour traiter de problématiques autour des paysages agricoles (introductio…
2019
National audience
Le marché de l'enseignement supérieur d'après les séries temporelles
1979
International audience