As natural disasters are induced by geodynamic activities or abnormal changes in the
environment, geological hazards tend to wreak havoc on the environment and human …

Advances in computing technology have fostered the development of new and powerful
deep learning (DL) techniques, which have demonstrated promising results in a wide range …

Pre-training by numerous image data has become de-facto for robust 2D representations. In
contrast, due to the expensive data processing, a paucity of 3D datasets severely hinders …

With the rapid development of deep learning technology and improvement in computing
capability, deep learning has been widely used in the field of hyperspectral image (HSI) …

Hyperspectral imaging (HSI) has been extensively utilized in many real-life applications
because it benefits from the detailed spectral information contained in each pixel. Notably …

In recent years, deep-learning-based hyperspectral image (HSI) classification methods have
achieved significant development. The superior capability of feature extraction from these …

Supervised machine learning and deep learning methods perform well in hyperspectral
image classification. However, hyperspectral images have few labeled samples, which …

Hyperspectral image (HSI) denoising plays an important role in image quality improvement
and related applications. Convolutional neural network (CNN)-based image denoising …

Deep neural networks have been widely applied to hyperspectral image (HSI) classification
areas, in which recurrent neural network (RNN) is one of the most typical networks. Most of …

In this article, we propose an efficient convolutional long short-term memory (ConvLSTM)
network with dual-direction transfer for pan-sharpening, termed D2TNet. We design a …