WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
Frontiers

An EEG-based machine learning framework for diagnosing acute sleep deprivation

Acute sleep deprivation significantly impacts cognitive function, contributes to accidents, and increases the risk of chronic illnesses, underscoring the need for reliable and objective diagnosis. Our ...
InfoWorld

AI and machine learning outside of Python

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.
Visual Studio Magazine

Tsetlin Machine Binary Classification Using C#

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
Frontiers

Generalised machine learning models outperform personalised models for cognitive load classification in real-life settings

Introduction: By issuing work-break reminders, for example, personal assistants for cognitive load could be beneficial in maintaining health and life satisfaction in society. Wearable sensors ...
Scientific Research Publishing

An Evaluation of Machine Learning Models for Threat Classification in IoT Devices ()

1 Center for Cyberspace Studies, Nasarawa State University, Keffi, Nigeria. 2 Department of Computer Engineering, Nile University of Nigeria, Abuja, Nigeria. 3 Department of Public and International ...
Scientific Research Publishing

Haghish, E.F. and Czajkowski, N. (2023) Reconsidering False Positives in Machine Learning Binary Classification Models of Suicidal Behavior. Current Psychology, 43, 10117-10121.

ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...
IEEE

Safe and Robust Binary Classification and Fault Detection Using Reinforcement Learning

Abstract: In this paper, we propose a learning-based method utilizing the Soft Actor-Critic (SAC) algorithm to train a binary Support Vector Machine (SVM) classifier. This classifier is designed to ...
IEEE

Binary Classification Aggregation Approaches to Technical Diagnostics with Application of Machine Learning

Abstract: The article investigates the specific features of binary classification aggregated methods application to solving the problems of technical diagnostics. The study found that the use of ...