p$^3$VAE: a physics-integrated generative model. Application to the semantic segmentation of optical remote sensing images. (arXiv:2210.10418v1 [cs.CV])

The combination of machine learning models with physical models is a recent
research path to learn robust data representations. In this paper, we introduce
p$^3$VAE, a generative model that integrates a perfect physical model which
partially explains the true underlying factors of variation in the data. To
fully leverage our hybrid design, we propose a semi-supervised optimization
procedure and an inference scheme that comes along meaningful uncertainty
estimates. We apply p$^3$VAE to the semantic segmentation of high-resolution
hyperspectral remote sensing …

application arxiv images physics remote segmentation semantic sensing