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 ...
IEEE

Deep Learning-Based Cascade Failure Prediction for Transmission Lines at Risk in an IoT-based Power Grid Monitoring Framework

Abstract: Under an internet of thing (IoT)-based framework, a power grid monitoring system can collect real-time transmission line data, which can then be used to predict the cascading failure risks ...
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 ...
City Journal

The Latest Attempt to Disprove the Sex Binary Falls Flat

A wave of pseudoscientific papers has tried to dismantle one of biology’s most fundamental truths: only two sexes exist, male and female. These papers often claim that sex is a broad “spectrum,” and ...
Scientific Research Publishing

Performance of Different Machine Learning Algorithms for Credit Risk Classification ()

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...
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 = ...
Scientific Research Publishing

Sen, P.C., Hajra, M. and Ghosh, M. (2019) Supervised Classification Algorithms in Machine Learning: A Survey and Review. In: Mandal, J.K. and Bhattacharya, D., Eds., Emerging ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...
Frontiers

Efficient tree species classification using machine and deep learning algorithms based on UAV-LiDAR data in North China

Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...
GitHub

binary-classification

Classified and clustered bank clients with respect to their user profile and decided if they should get credit. KNN & KMeans algorithms, K-Fold developed in C without libraries.