This workshop will consider several applications based on machine learning classification and the training of artificial neural networks and deep learning.
Introduction: Why Data Quality Is Harder Than Ever Data quality has always been important, but in today’s world of ...
Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...
In May 2025, the U.S. Army’s Soldier Lethality Project at the Picatinny Arsenal in New Jersey announced the official type classification of SIG Sauer’s M7 rifle and M250 automatic rifle, previously ...
Abstract: The classification of cognitive load is crucial to evaluate mental effort in various tasks. Compared to physiological measures such as electroencephalography (EEG), electrocardiography (ECG) ...
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The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...
This project aims to build a multi-class text classification model for consumer complaint narratives.It categorizes complaints into four classes: Credit Reporting, Debt Collection, Consumer Loan, and ...
Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
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 ...
ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...