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 ...
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...
The researchers suggest that this improvement in diagnostic performance for OFC biomarker discovery can be used to develop a diagnostic alternative for food allergy that is scalable and more efficient ...
Crop pests cause substantial yield losses worldwide and pose persistent challenges to sustainable agriculture.
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...
Atmospheric aerosols influence climate forcing, air quality, visibility, and human health, but their properties vary widely across space and time. Satellite instruments equipped with multi-angle and ...
From Deep Blue to modern AI, how chess exposed the shift from brute-force machines to learning systems, and why it matters AI ...
In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of ...
Future Market Insights (FMI) projects the Neural Processors Market to grow from USD 176 million in 2025 to USD 1,010 million by 2035, advancing at a 19.1% CAGR. This surge is being driven by the ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results