2 papers
cs.CV2025
Latent Dirichlet Transformer VAE for Hyperspectral Unmixing with Bundled Endmembers
Giancarlo Giannetti, Faisal Z. Qureshi
Hyperspectral images capture rich spectral information that enables per-pixel material identification; however, spectral mixing often obscures pure material signatures. To address…
cs.CV2024
SpACNN-LDVAE: Spatial Attention Convolutional Latent Dirichlet Variational Autoencoder for Hyperspectral Pixel Unmixing
Soham Chitnis, Kiran Mantripragada, Faisal Z. Qureshi
The hyperspectral pixel unmixing aims to find the underlying materials (endmembers) and their proportions (abundances) in pixels of a hyperspectral image. This work extends the Lat…