1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CV2023
Toulouse Hyperspectral Data Set: a benchmark data set to assess semi-supervised spectral representation learning and pixel-wise classification techniques
Romain Thoreau, Laurent Risser, Véronique Achard +2
Airborne hyperspectral images can be used to map the land cover in large urban areas, thanks to their very high spatial and spectral resolutions on a wide spectral domain. While th…
cs.CV2022★ 1 cited
Physics-informed Variational Autoencoders for Improved Robustness to Environmental Factors of Variation
Romain Thoreau, Laurent Risser, Véronique Achard +2
The combination of machine learning models with physical models is a recent research path to learn robust data representations. In this paper, we introduce pVAE, a variational…