Hyperspectral image classification (HSIC) has become a hot research topic. Hyperspectral
imaging (HSI) has been widely used in a wide range of real-world application areas due to …

Owing to rich spectral and spatial information, hyperspectral image (HSI) can be utilized for
finely classifying different land covers. With the emergence of deep learning techniques …

Deep learning models have shown great potential in remote sensing (RS) image processing
and analysis. Nevertheless, there are insufficient labeled samples to train deep networks …

The hyperspectral image (HSI) classification aims to assign each pixel to a land-cover
category. It is receiving increasing attention from both industry and academia. The main …

Although convolutional neural networks (CNNs) have shown superior performance to
traditional machine learning algorithms for hyperspectral image (HSI) classification tasks …

The deployment of convolutional neural networks (CNNs) to classify hyperspectral images is
extensively discussed in the research study. A number of different algorithms and …

Recently, deep learning models have achieved excellent performance in hyperspectral
image (HSI) classification. Among the many deep models, Transformer has gradually …

Deep-learning-based fault diagnosis of wind turbine has played a significant role in
advancing the renewable energy industry. However, the imbalanced data sampled by the …

Hyperspectral images (HSI) suffer from limited labeled data and the curse of dimensionality,
which makes it difficult to classify imbalanced and small-sized HSI data. To address the …

Hyperspectral image (HSI) classification is a vital task in hyperspectral image processing
and applications. Convolutional neural networks (CNN) are becoming an effective approach …