IEEE

Accurate and Efficient Fluid Flow Regime Classification Using Localized Texture Descriptors and Machine Learning

Abstract: This paper presents an image-based framework for classifying fluid flow regimes into low and high-speed states by utilizing spatially localized texture features combined with machine ...
Frontiers

Machine learning pipeline for microparticle size classification in self-mixing interferometric signals for flow cytometry

Self-mixing interferometry (SMI) is an emerging optical sensing technique for detecting and classifying microparticles in non-contact and label-free flowmetry applications. High precision and ...
Frontiers

Machine learning technique for the identification of two-phase (oil-water) flow patterns through pipelines

1 School of Mechanical Engineering, Universidad Industrial de Santander, Bucaramanga, Colombia 2 Industrial Multiphase Flow Laboratory (LEMI), Mechanical Engineering Department, São Carlos School of ...
IEEE

Supervised Machine Learning for Cell Classification in Microwave Flow Cytometers

Abstract: Microwave sensing of biological cells is of great interest for its noncontact, noninvasive nature and high-sensitivity, high-resolution potential. Nevertheless, the lack of measurement ...
Scientific Research Publishing

Machine Learning-Based Classification of Coronary Heart Disease: A Comparative Analysis of Logistic Regression, Random Forest, and Support Vector Machine Models ()

1 Department of Business Information System, Central Michigan University, Mount Pleasant, MI, USA. 2 Department of MPH, Central Michigan University, Mount Pleasant, MI, USA. 3 Department of ...
Scientific Research Publishing

Credit Score Classification Using Advanced Machine Learning: A Comprehensive Approach ()

1 Department of Computer Science, Rutgers University, New Brunswick, NJ, USA. 2 Department of Computer Science, Rochester Institute of Technology, Rochester, NY, USA. This paper presents a ...