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 …

Over the years, advances in sensor technologies have enhanced spatial, temporal, spectral,
and radiometric resolutions, thus significantly improving the size, resolution, and quality of …

Huge amounts of multimodal content and comments in a mixture form of text, image, and
emoji are continuously shared by users on various social networks. Most of the comments of …

The emergence of a convolutional neural network (CNN) has greatly promoted the
development of hyperspectral image (HSI) classification technology. However, the …

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 …

Recently, the field of hyperspectral image (HSI) classification is dominated by deep learning-
based methods. However, training deep learning models usually needs a large number of …

Background Although biopsy is the gold standard for tumour grading, being invasive, this
procedure also proves fatal to the brain. Thus, non-invasive methods for brain tumour …

Tree-based methods and deep neural networks (DNNs) have drawn much attention in the
classification of images. Interpretable canonical deep tabular data learning architecture …

Recently, ensemble multiple deep learning (DL) classifiers has been reported to be an
effective method for improving remote sensing classification accuracy. Although these …

Recently, collaborative representation classification (CRC) has attracted much attention for
hyperspectral image analysis. In particular, tangent space CRC (TCRC) has achieved …