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

Medical pattern classification using a novel binary similarity approach based on an associative classifier

Classification is a central task in machine learning, underpinning applications in domains such as finance, medicine, engineering, information technology, and biology. However, machine learning ...
IEEE

Fuzzy LASSO Logistic Regression: A Regularized Framework for Interpretable Binary Classification Under Uncertainty

Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...
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 = ...
EurekAlert!

Nighttime driving study reveals red light reduces motion sickness in automated vehicles

Shanghai, September 2025 — Motion sickness is a major barrier to passenger comfort, particularly during nighttime journeys when visual cues are limited. A new study published in Artificial ...
eLife

Fast evolutionary turnover and overlapping variances of sex-biased gene expression patterns defy a simple binary sex classification of somatic tissues

This study presents data on sex differences in gene expression across organs of four mice taxa. The authors have generated a unique and convincing dataset that fills a gap left by previous studies.
IEEE

Calibrating F1 Scores for Fair Performance Comparison of Binary Classification Models with Application to Student Dropout Prediction

Abstract: The F1 score has been widely used to measure the performance of machine learning models. However, it is variant to the ratio of the positive class in the training data, π. Depending on how ...