Accurate segmentation of medical images is essential for clinical decision-making, and deep learning techniques have shown remarkable results in this area. However, existing segmentation models that ...

Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...

This article is published by AllBusiness.com, a partner of TIME. A Convolutional Neural Network (CNN) represents a sophisticated advancement in artificial intelligence technology, specifically ...

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

Our research demonstrates that convolutional neural networks can significantly enhance the precision of nasal endoscopy interpretation. Achieving an average accuracy of 91.5% in localizing essential ...

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Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

Detecting concealed explosives and chemical threats constitutes a critical challenge in global security, yet current technologies often face significant operational limitations. While X-ray scanners ...