Business Insider

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 BEIJING, Feb.06, 2026––WiMi Hologram ...
GitHub

Network connectivity failure in test_spectral_embedding_trustworthiness with MNIST dataset loading

The test_spectral_embedding_trustworthiness [load_mnist-5000-0.8] test is sometimes failing due to a network connectivity issue when attempting to download the MNIST dataset from OpenML. The test ...
IEEE

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging

Abstract: Magnetic Particle Imaging (MPI) is an emerging imaging modality based on the magnetic response of superparamagnetic iron oxide nanoparticles to achieve high-resolution and real-time imaging ...
IEEE

A Microwave Photonic Processor for Convolutional Neural Networks With Increased Effective Speed of Convolution

Abstract: Due to the strong feature extraction capabilities, convolutional neural networks (CNNs) have been utilized for various tasks, including image recognition, object detection, and natural ...
INSPIRE

Exploring quantum neural networks for binary classification on MNIST dataset: A swap test approach

In this study, we propose a novel modularized Quantum Neural Network (mQNN) model tailored to address the binary classification problem on the MNIST dataset. The mQNN organizes input information using ...
GitHub

denisromanovskii/MNIST-linear-model

This project implements a linear neural network to recognize digits from the MNIST dataset. MNIST (Modified National Institute of Standards and Technology) is a widely used dataset for training and ...