3 citations · 3 across the 6 of their papers we have counts for
6 papers
CDG: Conditional Domain Generalization for Hyperspectral Imagery Classification with Convergence and Constrained-risk Theories
Zhe Gao, Bin Pan, Zhenwei Shi
Hyperspectral imagery (HSI) classification may suffer the challenge of hyperspectral-monospectra, where different classes present similar spectra. Joint spatial-spectral feature ex…
Domain Generalization Guided by Large-Scale Pre-Trained Priors
Zongbin Wang, Bin Pan, Shiyu Shen +2
Domain generalization (DG) aims to train a model from limited source domains, allowing it to generalize to unknown target domains. Typically, DG models only employ large-scale pre-…
Domain Agnostic Conditional Invariant Predictions for Domain Generalization
Zongbin Wang, Bin Pan, Zhenwei Shi
Domain generalization aims to develop a model that can perform well on unseen target domains by learning from multiple source domains. However, recent-proposed domain generalizatio…
RSMamba: Remote Sensing Image Classification with State Space Model
Keyan Chen, Bowen Chen, Chenyang Liu +3
Remote sensing image classification forms the foundation of various understanding tasks, serving a crucial function in remote sensing image interpretation. The recent advancements…
Learning to detect cloud and snow in remote sensing images from noisy labels
Zili Liu, Hao Chen, Wenyuan Li +5
Detecting clouds and snow in remote sensing images is an essential preprocessing task for remote sensing imagery. Previous works draw inspiration from semantic segmentation models…
Bayesian Domain Invariant Learning via Posterior Generalization of Parameter Distributions
Shiyu Shen, Bin Pan, Tianyang Shi +2
Domain invariant learning aims to learn models that extract invariant features over various training domains, resulting in better generalization to unseen target domains. Recently,…