AI-native air interfaces represent a shift from mathematical models to learned representations at the PHY layer.

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...

A new artificial intelligence approach combines deep learning with physical modeling to extract detailed aerosol properties from complex satellite observations. By learning how light intensity and ...

Researchers at Chungnam National University have developed a deep learning method that predicts stable defect configurations in nematic liquid crystals in milliseconds rather than hours. This rapid ...

Recent research (2024-2025) consistently demonstrates the advantages of integrated AI-VR training: Knowledge Acquisition: ...

Order doesn’t always form perfectly—and those imperfections can be surprisingly powerful. In materials like liquid crystals, ...

School of Chemical Engineering and Technology, State Key Laboratory of Chemical Engineering, Tianjin University, Tianjin 300072, China Haihe Laboratory of Sustainable Chemical Transformations, Tianjin ...

An important but unresolved question in deep learning for EEG decoding is which features neural networks learn to solve the task. Prior interpretability studies have mainly explained individual ...

Abstract: This letter proposes a deep learning-based inverse design framework for two-port electromagnetic(EM) structures, which synergistically integrates deep residual neural networks (ResNet) with ...

This project presents a complete workflow for cone detection in Formula Student Driverless scenarios using deep learning. It demonstrates how to use MATLAB® and Simulink® for data preparation and ...