WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification

WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification BEIJING, Jan. 15, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global ...
IEEE

Unified Twin Support Vector Machines for Large-Scale Pattern Classification

Abstract: Over the years, researchers have proposed numerous Twin Support Vector Machines (TSVM) variants aimed at addressing diverse challenges. These variants encompass sparse TSVM models, robust ...
Scientific Research Publishing

Brereton, R.G. and Lloyd, G.R. (2010) Support Vector Machines for Classification and Regression. The Analyst, 135, 230-267.

ABSTRACT: Support vector regression (SVR) and computational fluid dynamics (CFD) techniques are applied to predict the performance of an automotive torque converter in the design process of turbine ...
Frontiers

Migraine triggers, phases, and classification using machine learning models

1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States 2 Independent Researcher, Monmouth County, NJ, United States Background: In many countries, patients with headache disorders ...
Scientific Research Publishing

Research on Credit Risk Rating of Commercial Banks Based on Support Vector Machine

In the era of big data and artificial intelligence, machine learning is one of the hot issues in the field of credit rating. On the basis of combing the literature on credit rating methods at home and ...
IEEE

Manifold Energy Projection Twin Support Vector Machine for Semi-Supervised Classification

Abstract: The Projection Twin Support Vector Machine (PTSVM) and its variant, the Least Squares PTSVM (LSPTSVM), have demonstrated significant effectiveness in supervised classification tasks due to ...
Frontiers

Support Vector Machine Analysis of Functional Magnetic Resonance Imaging of Interoception Does Not Reliably Predict Individual Outcomes of Cognitive Behavioral Therapy in Panic ...

Background: The approach to apply multivariate pattern analyses based on neuro imaging data for outcome prediction holds out the prospect to improve therapeutic decisions in mental disorders. Patients ...