Big Data and machine learning (ML) technologies have the potential to impact many facets
of environment and water management (EWM). Big Data are information assets …

Modern hyperspectral imaging systems produce huge datasets potentially conveying a great
abundance of information; such a resource, however, poses many challenges in the …

Hyperspectral image (HSI) classification has attracted wide attention in many fields.
Applying Graph Neural Network (GNN) to HSI classification is one of the research frontiers …

Recently, the graph convolutional network (GCN) has drawn increasing attention in the
hyperspectral image (HSI) classification. Compared with the convolutional neural network …

Registration for multisensor or multimodal image pairs with a large degree of distortions is a
fundamental task for many remote sensing applications. To achieve accurate and low-cost …

The rapid worldwide spread of Coronavirus Disease 2019 (COVID-19) has resulted in a
global pandemic. Correct facemask wearing is valuable for infectious disease control, but …

Due to the unique feature of the three-dimensional convolution neural network, it is used in
image classification. There are some problems such as noise, lack of labeled samples, the …

Hyperspectral image (HSI) classification aims to assign each hyperspectral pixel with a
proper land-cover label. Recently, convolutional neural networks (CNNs) have shown …

Convolutional neural networks (CNN) have led to a successful breakthrough for
hyperspectral image classification (HSIC). Due to the intrinsic spatial-spectral specificities of …

Deep learning methods, especially convolutional neural network (CNN)-based methods,
have shown promising performance for hyperspectral image (HSI) change detection (CD). It …