Hierarchical joint classification models for multi-resolution, multi-temporal and multi-sensor remote sensing images. Application to natural disasters

Leaf morphological and anatomical traits variation of Artemisia herba-alba in a steppe zone of Algeria Khadidja Abderabbi, Ahmed Adda, Hachemi Benhassaini, Othmane Merah.. To cite

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In order to improve the convergence, we propose in this paper an accelerated spectral approach, which consists in modelling the problem by a fluid-loaded shell

Cette construction du caract`ere de Chern (qui sera rendu rigoureuse, voir §4.2), sera notre source prin- cipale d’inspiration, et l’objectif de ce travail consiste essentiellement `

In this section we introduce STEGON , our attention-based spatial convolutional graph neural network especially tailored to deal with the land cover mapping task... The Region

We introduce in this work the DL-based HOb2sRNN (Hierarchical Object based two-Stream Recurrent Neural Network) architecture in order to deal with land cover mapping at object

More in detail, the additional information is firstly employed to learn a (teacher) multi-source model and, successively, a mono-source (student) model is trained consid- ering

One difference between HTN planners and generative planners is on the way their plans are generated. HTN planners build plans by systematically decomposing all tasks while