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 ...
European Medical Journal

Lightweight Neural Networks Improve Lung Cancer Diagnosis

Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...
Visual Studio Magazine

Binary Classification Using a scikit Neural Network

Machine learning with neural networks is sometimes said to be part art and part science. Dr. James McCaffrey of Microsoft Research teaches both with a full-code, step-by-step tutorial. A binary ...
InfoWorld

The most popular neural network styles and how they work

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...
Tech Xplore

New graph attention network models higher-order relationships in complex graph data

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
EurekAlert!

Transfer learning empowers material Z classification with muon tomography

Researchers have demonstrated, for the first time, that transfer learning can significantly enhance material Z-class identification in muon tomography, even in scenarios with limited or completely ...
Visual Studio Magazine

Binary Classification Using a scikit Neural Network

A binary classification problem is one where the goal is to predict the value of a variable where there are exactly two discrete possibilities. For example, you might want to predict the sex of a ...