Abstract: In many different fields, Support Vector Machines (SVMs) have shown to be an effective tool for regression and classification problems. When using support vector machines (SVMs), the kernel ...

Abstract: Noisy data is ubiquitous in quantum computer, greatly affecting the performance of various algorithms. However, existing quantum support vector machine models are not equipped with ...

Ms. Mutcherson is a professor at Rutgers Law School. Right now in an Atlanta hospital room lies a 30-year-old nurse and mother, Adriana Smith. Ms. Smith, who is brain-dead, has been connected to life ...

Support Vector Machines (SVMs) are a powerful and versatile supervised machine learning algorithm primarily used for classification and regression tasks. They excel in high-dimensional spaces and are ...

(CGCSTCD'2017) An easy, flexible, and accurate plate recognition project for Chinese licenses in unconstrained situations. CGCSTCD = China Graduate Contest on Smart-city Technology and Creative Design ...

The purpose is to explore the feature recognition, diagnosis, and forecasting performances of Semi-Supervised Support Vector Machines (S3VMs) for brain image fusion Digital Twins (DTs). Both unlabeled ...

Non-invasive measurements of brain function and structure as neuroimaging in patients with mental illnesses are useful and powerful tools for studying discriminatory biomarkers. To date, functional ...

Central Department of Computer Science and Information Technology (CDCSIT), Tribhuvan University, Kirtipur, Nepal. The term Named Entity (NE) was evolved during the sixth Message Understanding ...