IEEE

QFARE: Quantum Feedforward Adaptive Reinforcement Ensemble for MNIST Classification

Abstract: We introduce QFARE, a hybrid quantum-classical architecture for MNIST digit classification. Our approach employs a classical variational autoencoder (VAE) to compress 28×28 grayscale images ...
IEEE

Enhancing Fashion-MNIST classification accuracy: A study of regularised least squares and kernelbased approaches

Abstract: We explore the application of Least Squares (LS) classifiers for image classification on the Fashion MNIST dataset. To address the challenges of overlapping feature classes, regularisation ...
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 ...