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 ...

Interpretability in deep learning for finance: A case study for the Heston model

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 ...
AZoOptics

Deep Learning in Optical Microscopy: Advancements and Applications

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.

AI model accelerates defect-based material design

Across the physical world, many intricate structures form via symmetry breaking. When a system with inherent symmetry ...
IEEE

KAST-Net: An Inversion Network with Gravity Kernel Matrix Layers for Joint Gravity and Gradients

Abstract: Gravity inversion, as a critical technique in gravity exploration, is widely used for reconstructing three-dimensional (3-D) subsurface density structures in mineral resource exploration, ...
Frontiers

Exploring physical and functional EEG connectivity with multilayer graph transformer convolutional networks for emotion recognition

1 School of Automation, Nanjing University of Science and Technology, Nanjing, Jiangsu, China 2 School of Engineering, University of Birmingham, Birmingham, United Kingdom Electroencephalogram ...
Palm Beach Post

DeepForest AI unlocks hidden forest layers

GA, UNITED STATES, January 9, 2026 /EINPresswire.com/ — Forests hide critical ecological information beneath dense canopy layers, where traditional imaging ...
IEEE

Multigranularity Deep Graph Convolutional Neural Network Node Clustering Leveraging Spatial Information

Abstract: In the era of information explosion, clustering analysis of graph-structured data and empty graph-structured data is of great significance for extracting the intrinsic value of data. From ...