SPIN: Simplifying Polar Invariance for Neural networks Application to vision-based irradiance forecasting

Quentin Paletta (1, 2) , Anthony Hu (1) , Guillaume Arbod (2) , Philippe Blanc (3) , Joan Lasenby (1)

1 CAM - University of Cambridge [UK]
2 ENGIE Lab CRIGEN
3 O.I.E. - Centre Observation, Impacts, Énergie

Domaines: Sciences de l'ingénieur [physics]; Planète et Univers [physics]; Océan, Atmosphère; Mathématiques [math]; Mathématiques appliquées

Quentin Paletta, Anthony Hu, Guillaume Arbod, Philippe Blanc, Joan Lasenby. SPIN: Simplifying Polar Invariance for Neural networks Application to vision-based irradiance forecasting. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Jun 2022, New Orleans, France. pp.5178-5187, ⟨10.1109/CVPRW56347.2022.00566⟩. ⟨hal-03922652⟩