V. Jacq and S. Balaguer, Neige ne plaine sur la Ferance méditerranéenne. Phénomènes remarquable n°10. Publication Météo-France

N. Jacobs, W. Burgin, N. Fridrich, A. Abrams, K. Miskell et al., The global network of outdoor webcams: Properties and applications, Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ser. GIS '09, pp.111-120, 2009.

M. Kosmala, K. Hufkens, and A. D. Richardson, Integrating camera imagery, crowdsourcing, and deep learning to improve high-frequency automated monitoring of snow at continental-to-global scales, PLOS ONE, vol.13, issue.12, pp.1-19, 2018.
URL : https://hal.archives-ouvertes.fr/hal-02621651

M. Wang, S. Korayem, D. J. Blanco, and . Crandall, Tracking natural events through social media and computer vision, Proceedings of the 24th ACM international conference on Multimedia, pp.1097-1101, 2016.

W. Chu, X. Zheng, and D. Ding, Camera as weather sensor: Estimating weather information from single images, journal of Visual Communication and Image Representation, vol.46, pp.233-249, 2017.

M. Elhoseiny, S. Huang, and A. Elgammal, Weather classifcation with deep convolutional neural networks, 2015 IEEE International Conference on Image Processing (ICIP), pp.3349-3353, 2015.

W. Chu, K. Ho, and A. Borji, Visual weather temperature prediction" CoRR, 2018.

S. G. Narasimhan and S. K. Nayar, Vision and the atmosphere, International Journal of Computer Vision, vol.48, issue.3, pp.233-254, 2002.

H. Zhou, B. Gao, and J. Wu, Sunrise or sunset: Selective comparison learning for subtle attribute recognition, CoRR, 2017.

Y. You, C. Lu, W. Wang, and C. Tang, Relative cnn-rnn: Learning relative atmospheric visibility from images, IEEE Transactions on Image Processing, vol.28, issue.1, pp.45-55, 2019.

C. Lu, D. Lin, J. Jia, and C. Tang, Two-class weather classification, The IEEE Conference on Computer Vision and Pattern Recognition

D. Glasner, P. Fua, T. Zickler, and L. Zelnik-manor, Hot or not: Exploring correlations between appearance and temperature, 2015 IEEE International Conference on Computer Vision (ICCV), vol.00, pp.3997-4005, 2015.

D. Lin, C. Lu, H. Huang, and J. Jia, Rscm: Region selection and concurrency model for multi-class weather recognition, IEEE Transactions on Image Processing, vol.26, issue.9, pp.4154-4167, 2017.

K. He, X. Zhang, S. Ren, and J. Sun, Deep residual learning for image recognition, Proceedings of the IEEE conference on computer vision and pattern recognition, pp.770-778, 2016.

K. Simonyan and A. Zisserman, Very deep convolutional networks for large-scale image recognition, 2014.

N. Graves and S. Newsam, Camera-based visibility estimation: Incorporating multiple regions and unlabeled observations, Ecological informatics, vol.23, pp.62-68, 2014.

A. Volokitin, R. Timofte, and L. Van-gool, Deep features or not: Temperature and time prediction in outdoor scenes, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.63-71, 2016.

, ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate . Copernicus Climate Change Service Climate Data Store (CDS), Copernicus Climate Change Service, issue.C3S, 2017.

D. Sculley, Combined regression and ranking, Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, pp.979-988, 2010.

X. Wang, K. He, and A. Gupta, Transitive invariance for self-supervised visual representation learning, Proceedings of the IEEE international conference on computer vision, pp.1329-1338, 2017.

D. P. Kingma and J. Ba, Adam: A method for stochastic optimization, 2014.