Blue carbon (BC) ecosystems are an important coastal resource, as they provide a range of
goods and services to the environment. They play a vital role in the global carbon cycle by …

Hyperspectral image classification (HSIC) is essential in remote sensing image analysis.
Applying a graph neural network (GNN) to hyperspectral image (HSI) classification has …

So far, a large number of advanced techniques have been developed to enhance and
extract the spatially semantic information in hyperspectral image processing and analysis …

Dimensionality reduction (DR) is an important way of improving the classification accuracy of
a hyperspectral image (HSI). Graph learning, which can effectively reveal the intrinsic …

In recent years, airborne and spaceborne hyperspectral imaging systems have advanced in
terms of spectral and spatial resolution, which makes the data sets they produce a valuable …

In this paper, we propose a new method for hyperspectral images (HSI) classification,
aiming to take advantage of both manifold learning‐based feature extraction and neural …

This work proposes a new shadow restoration method for hyperspectral images based on
nonlinear unmixing. A physical model is introduced to estimate the shadowed spectrum from …

With the rapid growth of installed capacity of photovoltaic power systems, status monitoring
and fault diagnosis of PV arrays becomes increasingly important for improving the energy …

The inclusion of spatial information into spectral classifiers for fine-resolution hyperspectral
imagery has led to significant improvements in terms of classification performance. The task …

The digitization and automation of the raw material sector is required to attain the targets set
by the Paris Agreements and support the sustainable development goals defined by the …