Minkang Zhang Improves Medical Image Recognition Through RNN Optimization and Deep Learning Integration

A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN ...

Adaptive method helps light-based quantum processors act more like neural networks

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...
TMCnet

MicroCloud Hologram Inc. Releases Next-Generation Quantum Convolutional Neural Network Multi-Class Classification Technology, Driving Quantum Machine Learning Towards ...

SHENZHEN, China, Nov. 14, 2025 /PRNewswire/ -- MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, has launched a groundbreaking technological ...
optics.org

Rome-led group progresses toward practical photonic quantum neural networks

Photons are fast, stable, and easy to manipulate on chips, making photonic systems a promising platform for QCNNs. However, ...
Forbes

A Quantum Leap In AI: IonQ Aims To Create Quantum Machine Learning Models At The Level Of General Human Intelligence

Classical machine learning (ML) is a powerful subset of artificial intelligence. Machine learning has advanced from simple pattern recognition in the 1960s to today's advanced use of massive datasets ...
Time

Machine Learning

This article is published by AllBusiness.com, a partner of TIME. Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on enabling computers to learn from data and improve ...
eWeek

Generative AI vs Machine Learning: Key Differences and Use Cases

eSpeaks host Corey Noles sits down with Qualcomm's Craig Tellalian to explore a workplace computing transformation: the rise of AI-ready PCs. Matt Hillary, VP of Security and CISO at Drata, details ...