In modern‐day medicine, medical imaging has undergone immense advancements and can
capture several biomedical images from patients. In the wake of this, to assist medical …

Kernel methods and deep learning are two of the most currently remarkable machine
learning techniques that have achieved great success in many applications. Kernel methods …

With the growth of online shopping, Credit Card Fraud (CCF) comes out as a serious
menace. For this end, the automatic and real-time fraud detection field calls for several …

The rise of machine learning increases the current computing capabilities and paves the
way to novel disruptive applications. In the current era of big data, the application of image …

The collected data from industrial machines are often imbalanced, which poses a negative
effect on learning algorithms. However, this problem becomes more challenging for a mixed …

Kernel-based support vector machines (SVMs) are supervised machine learning algorithms
for classification and regression problems. We introduce a method to train SVMs on a D …

Sign language is a natural, visually oriented and non-verbal communication channel
between people that facilitates communication through facial/bodily expressions, postures …

This work presents a computer-aided framework for allergy diagnosis which is capable of
handling comorbidities. The system was developed using datasets collected from allergy …

The integration of intelligent system mainly includes the application of intelligent technology,
such as artificial intelligence and computational intelligence method, which is used in …

Abstract Human Activity Recognition (HAR) has emerged as a major player in this era of
cutting-edge technological advancement. A key role that HAR plays is its ability to remotely …