EurekAlert!

Meta-optics enabling highly scalable machine vision

Neural networks (NNs) have emerged as a powerful paradigm across diverse scientific and technological domains, instigating transformative advancements in areas such as drug discovery, image processing ...
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 ...
Nasdaq

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 ...
Scientific Research Publishing

Pedamonti, D. (2018) Comparison of Non-Linear Activation Functions for Deep Neural Networks on MNIST Classification Task. arXiv.

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...
GitHub

number-classification

A public API for HNG Stage 1 task that classifies a given number by identifying its mathematical properties (prime, perfect, Armstrong, parity, digit sum) and retrieves a fun fact using the Numbers ...