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Published at November 22

Physically Interpretable Probabilistic Domain Characterization

cs.CV

cs.AI

eess.IV

Released Date: November 22, 2024

Authors: Anaïs Halin¹, Sébastien Piérard¹, Renaud Vandeghen¹, Benoît Gérin², Maxime Zanella², Martin Colot³, Jan Held¹, Anthony Cioppa¹, Emmanuel Jean⁴, Gianluca Bontempi³, Saïd Mahmoudi⁵, Benoît Macq², Marc Van Droogenbroeck¹

Aff.: ¹Montefiore Institute, University of Liège (ULiège), Liège, Belgium; ²Catholic University of Louvain (UCLouvain), Louvain-la-Neuve, Belgium; ³Université Libre de Bruxelles (ULB), Brussels, Belgium; ⁴Multitel research & innovation centre, Mons, Belgium; ⁵University of Mons (UMons), Mons, Belgium

Arxiv: http://arxiv.org/abs/2411.14827v1

parameter	range	predicted
cloudiness	$0$ to $100\%$	yes
fog density	$0$ to $100\%$	yes
precipitation	$0$ to $100\%$	yes
sun azimuth angle	$0^{\circ}$ to $360^{\circ}$	no
sun altitude angle	$-90^{\circ}$ to $90^{\circ}$	yes
wind intensity	$0$ to $100\%$	yes
precipitation deposits	$0$ to $100\%$	yes