Deep learning has recently attracted significant attention in the field of hyperspectral images
(HSIs) classification. However, the construction of an efficient deep neural network mostly …

Recent years have witnessed the quick progress of the hyperspectral images (HSI)
classification. Most of existing studies either heavily rely on the expensive label information …

Abstract Support Vector Machine (SVM) stands out as a prominent machine learning
technique widely applied in practical pattern recognition tasks. It achieves binary …

Support Vector Machine (SVM) has always been one of the most successful learning
algorithms, with the central idea of maximizing the minimum margin, ie, the smallest distance …

In this paper, we propose a new method for image classification by the content in
heterogeneous databases. This approach is based on the use of new series of separable …

The explosion of the Internet has deeply affected the labour market. Identifying most
rewarded and demanded items in job offers is key for recruiters and candidates. This work …

Accurate classification of Electroencephalogram (EEG) signals plays an important role in
diagnoses of different type of mental activities. One of the most important challenges …

Recently, deep neural networks have made significant breakthroughs in the image super-
resolution (SR) field. Most deep learning-based image SR methods learn an end-to-end …

Using binary classification techniques to perform multi-class classification of data is still of
great practical interest due to the robustness and simplicity of binary classifiers. These …

(1) Background: Avatar Therapy (AT) is currently being studied to help patients suffering
from treatment-resistant schizophrenia. Facilitating annotations of immersive verbatims in AT …