2 citations · 2 across the 4 of their papers we have counts for
4 papers
Hyperspectral Diffusion Equivariant Imaging (HyDiff-EI): A Self-supervised Framework for Hyperspectral Image Inpainting
Shuo Li, Mike Davies, Mehrdad Yaghoobi
A novel Hyperspectral diffusion Equivariant Imaging (HyDiff-EI) framework for solving the hyperspectral image (HSI) inpainting problem has been presented here. Unlike conventional…
Equivariant Imaging for Self-supervised Hyperspectral Image Inpainting
Shuo Li, Mike Davies, Mehrdad Yaghoobi
Hyperspectral imaging (HSI) is a key technology for earth observation, surveillance, medical imaging and diagnostics, astronomy and space exploration. The conventional technology f…
Self-Supervised Hyperspectral Inpainting with the Optimisation inspired Deep Neural Network Prior
Shuo Li, Mehrdad Yaghoobi
Hyperspectral Image (HSI)s cover hundreds or thousands of narrow spectral bands, conveying a wealth of spatial and spectral information. However, due to the instrumental errors and…
Amortised Invariance Learning for Contrastive Self-Supervision
Ruchika Chavhan, Henry Gouk, Jan Stuehmer +3
Contrastive self-supervised learning methods famously produce high quality transferable representations by learning invariances to different data augmentations. Invariances establi…