Hyperspectral

A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration

Bayesian Unmixing of Hyperspectral Image Sequence With Composite Priors for Abundance and Endmember Variability

CoSpace: Common Subspace Learning from Hyperspectral-Multispectral Correspondences

Cross-Attention in Coupled Unmixing Nets for Unsupervised Hyperspectral Super-Resolution

CyCU-Net: Cycle-Consistency Unmixing Network by Learning Cascaded Autoencoders

Deep Encoder–Decoder Networks for Classification of Hyperspectral and LiDAR Data

Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyperspectral Unmixing

Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep (Overview and Toolbox)

Hyperspectral Image Classification—Traditional to Deep Models: A Survey for Future Prospects

Hyperspectral Image Super-Resolution via Deep Spatiospectral Attention Convolutional Neural Networks

Hyperspectral Imagery Classification via Random Multi-Graphs Ensemble Learning

Hyperspectral Pansharpening Based on Improved Deep Image Prior and Residual Reconstruction

l₀-l₁ Hybrid Total Variation Regularization and Its Applications on Hyperspectral Image Mixed Noise Removal and Compressed Sensing

Learnable Manifold Alignment (LeMA) : A Semi-supervised Cross-modality Learning Framework for Land Cover and Land Use Classification

Learning Locality-Constrained Sparse Coding for Spectral Enhancement of Multispectral Imagery

Learning Tensor Low-Rank Representation for Hyperspectral Anomaly Detection

MiSiCNet: Minimum Simplex Convolutional Network for Deep Hyperspectral Unmixing

Multimodal Hyperspectral Unmixing: Insights from Attention Networks

Multimodal Hyperspectral Unmixing: Insights From Attention Networks

NonRegSRNet: a Non-rigid Registration Hyperspectral Super-Resolution Network

Revisiting Deep Hyperspectral Feature Extraction Networks via Gradient Centralized Convolution

Semisupervised Cross-Scale Graph Prototypical Network for Hyperspectral Image Classification

SGML: A Symmetric Graph Metric Learning Framework for Efficient Hyperspectral Image Classification

Sparsity-Enhanced Convolutional Decomposition: A Novel Tensor-Based Paradigm for Blind Hyperspectral Unmixing

Spectral Superresolution of Multispectral Imagery With Joint Sparse and Low-Rank Learning

Spectralformer: Rethinking hyperspectral image classification with transformers

Tensor Low-Rank Constraint and l0 Total Variation for Hyperspectral Image Mixed Noise Removal

Unsupervised and Unregistered Hyperspectral Image Super-Resolution With Mutual Dirichlet-Net

Unsupervised Feature-Learning for Hyperspectral Data with Autoencoders