As the regulation on the surface web becomes more stringent, criminals are gradually
turning to the darknet markets for illicit operations. Moderating and studying the content on …

In recent years, transformer-based models have played a significant role in advancing
language modeling for natural language processing. However, they require substantial …

The ever-growing landscape of Internet of Things (IoT) technology and the evolution of deep
learning algorithms have ushered in transformative changes in the communication strategy …

This paper presents a novel approach for the recognition of multiple sclerosis (MS) using
wavelet entropy and a Particle Swarm Optimization (PSO)-based neural network. MS is a …

This study navigates the intricate landscape of sarcasm detection within the condensed
confines of newspaper titles, addressing the nuanced challenge of decoding layered …

Recent developments in the area of research on sign language recognition have led to
making use of deep learning techniques with the goal to assist the self-learning transition of …

This paper explores using semi-supervised learning and Graph Convolutional Networks
(GCNs) in mobile text translation. It delves into the challenges of mobile translation …

Multilingual information retrieval using graph neural networks offers practical applications in
English translation by leveraging advanced computational models to enhance the efficiency …