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Found 3 papers, 3 papers with code
Local-Global Transformer Enhanced Unfolding Network for Pan-sharpening
Moreover, we customize a Local-Global Transformer (LGT) to simultaneously model local and global dependencies, and further formulate an LGT-based prior module for image denoising.
Adaptive Mask Sampling and Manifold to Euclidean Subspace Learning with Distance Covariance Representation for Hyperspectral Image Classification
Subsequently, based on distance covariance descriptor, a dual channel distance covariance representation (DC-DCR) module is proposed for modeling unified spectral-spatial feature representations and exploring spectral-spatial relationships, especially linear and nonlinear interdependence in spectral domain.
Ranked #1 on
Hyperspectral Image Classification
on Indian Pines
(OA@5%perclass metric)
Hyperspectral image analysis
Hyperspectral Image Classification
+1
Exploring the Relationship between Center and Neighborhoods: Central Vector oriented Self-Similarity Network for Hyperspectral Image Classification
Specifically, based on two similarity measures, we firstly design an adaptive weight addition based spectral vector self-similarity module (AWA-SVSS) in input space and a Euclidean distance based feature vector self-similarity module (ED-FVSS) in feature space to fully mine the central vector oriented spatial relationships.
Ranked #1 on
Hyperspectral Image Classification
on Indian Pines
(OA@10%perclass metric)
Hyperspectral image analysis
Hyperspectral Image Classification
+1
