4 papers
A Copula-Guided Temporal Dependency Method for Multitemporal Hyperspectral Images Unmixing
Ruiying Li, Bin Pan, Qiaoying Qu +2
Multitemporal hyperspectral unmixing (MTHU) aims to model variable endmembers and dynamical abundances, which emphasizes the critical temporal information. However, existing method…
SMILE: A Super-resolution Guided Multi-task Learning Method for Hyperspectral Unmixing
Ruiying Li, Bin Pan, Qiaoying Qu +2
The performance of hyperspectral unmixing may be constrained by low spatial resolution, which can be enhanced using super-resolution in a multitask learning way. However, integrati…
Preserving Domain Generalization in Fine-Tuning via Joint Parameter Selection
Bin Pan, Shiyu Shen, Zongbin Wang +2
Domain generalization seeks to develop models trained on a limited set of source domains that are capable of generalizing effectively to unseen target domains. While the predominan…
Multitemporal Latent Dynamical Framework for Hyperspectral Images Unmixing
Ruiying Li, Bin Pan, Lan Ma +2
Multitemporal hyperspectral unmixing can capture dynamical evolution of materials. Despite its capability, current methods emphasize variability of endmembers while neglecting dyna…