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 ...
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 ...
Visual Studio Magazine

Multi-Class Classification Using a scikit Neural Network

Dr. James McCaffrey of Microsoft Research says a neural network model is arguably the most powerful multi-class classification technique. A multi-class classification problem is one where the goal is ...
Semiconductor Engineering

Spiking Neural Networks: Hardware & Algorithm Developments

A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...
TMCnet

MicroCloud Hologram Inc. Achieves Breakthrough in Practically Deployable Quantum Recurrent Neural Network (QRNN) Technology Oriented Toward Sequential Learning

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released a core quantum machine learning technology oriented toward sequential learning tasks—the ...
Science Daily

Training algorithm breaks barriers to deep physical neural networks

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...
ascopubs.org

Analytical Validation of a Deep Neural Network Algorithm for the Detection of Ovarian Cancer

Early detection of ovarian cancer, the deadliest gynecologic cancer, is crucial for reducing mortality. Current noninvasive risk assessment measures include protein biomarkers in combination with ...
Semiconductor Engineering

Convolutional Neural Networks: Co-Design of Hardware Architecture and Compression Algorithm

“Over the past decade, deep-learning-based representations have demonstrated remarkable performance in academia and industry. The learning capability of convolutional neural networks (CNNs) originates ...
Technology Networks

Machine Learning Applications in Proteomics

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.
pv magazine International

PV energy forecasting based on genetic algorithms, dynamic neural network

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...