Data classification is a key domain of research in real-world applications. One of the big
challenges of real-world data classification is to tackle the presence of noise and outliers. In …

The main objective of twin support vector regression (TSVR) is to find the optimum
regression function based on the ε-insensitive up-and down-bound with equal influences on …

Diabetes is one of the most prevalent non-communicable diseases and is the 6th leading
cause of death worldwide. It'sa chronic metabolic disorder which has no cure, however, it is …

Due to the increasing popularity of support vector machine (SVM) and the introduction of
Universum, many variants of SVM along with Universum such as Universum support vector …

Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder that affects an
individual's sensory activity, social interaction, and cognitive abilities. In the mental illnesses …

To improve the generalization performance, we develop a new technique for handling the
impacts of outliers using Lagrangian twin bounded SVM (TBSVM) with kernel fuzzy …

Maritime surveillance contributes in the security of ports, oil platforms, and coastal littoral by
detecting unusual activities such as unlicensed fishing boats, pirate attacks, and human …

Summary Using Artificial Intelligence (AI) in Autonomous Finance (AF) helps reduce error
and biases caused by humans. By automating duties and functions previously performed …

Target Detection has entered into various practical implementations in various fields,
including healthcare, military and defense, autonomous driving, pedestrian detection …

Anomaly detection in surveillance videos is a crucial task for ensuring public safety and
security. Traditional methods rely on rule-based or handcrafted feature-based approaches …