Electrical and Electronic Engineering

A Structural Subspace Clustering Approach for Hyperspectral Band Selection

Spectral feature fusion networks with dual attention for hyperspectral image classification

Recent progress in spectral classification is largely attributed to the use of convolutional neural networks (CNN). While a variety of successful architectures have been proposed, they all extract spectral features from various portions of adjacent …

Hybrid-Hypergraph Regularized Multiview Subspace Clustering for Hyperspectral Images

Subspace Clustering for Hyperspectral Images via Dictionary Learning with Adaptive Regularization

Deep feature fusion via two-stream convolutional neural network for hyperspectral image classification

The representation power of convolutional neural network (CNN) models for hyperspectral image (HSI) analysis is in practice limited by the available amount of the labeled samples, which is often insufficient to sustain deep networks with many …

MRI Reconstruction Using Markov Random Field and Total Variation as Composite Prior