COVID-19 is a newly identified disease, which is very contagious and has been rapidly
spreading across different countries around the world, calling for rapid and accurate …

Machine Learning is seeing its growth more rapidly in this decade. Many applications and
algorithms evolve in Machine Learning day to day. One such application found in journals is …

Image anomaly detection is an application-driven problem where the aim is to identify novel
samples, which differ significantly from the normal ones. We here propose Pyramidal Image …

Introduction Assessing the possibility of patient discharge based on data-mining models is
one of the common, user-friendly approaches to optimally exploit the limited capacity of …

Existing meta-learning based few-shot learning (FSL) methods typically adopt an episodic
training strategy whereby each episode contains a meta-task. Across episodes, these tasks …

Students are one of the substances that need to be considered in relation to the world of
education, because students are translators of the dynamics of science, and carry out the …

Background: One of the early screening methods of breast cancer that is still used today is
mammogram due to its low cost. Unfortunately, this low cost accompanied with low …

In the digital age, many applications can benefit from collecting data. Classification
algorithms, for example, are used to predict the class labels of samples (also termed data …

Image extraction based on image attributes is one of the emerging fields in image
processing. Today, most of the retrieval process is done with help of image attributes …

Image classification is an important and fundamental task in computer vision and machine
learning. The task is to classify images into one of some pre-defined groups based on the …