Frontiers

Graph Learning and Deep Unfolding for Electromagnetic Field Modelling and Antenna Systems

Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...

Fundamental emerges from stealth with first major foundation model trained for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...

Baidu’s Robin Li on China’s push to diffuse AI throughout society

Robin Li spoke to TIME about the AI ambitions of Baidu and China.
Que.com on MSN

Top 5 AI stocks to watch for future gains 2026

Artificial intelligence continues to revolutionize industries, and the financial markets are no exception. AI stocks offer ...
IEEE

DeepFake Detection for Military Security: A Deep Learning Approach Using TensorFlow and CNN Architecture

Abstract: Military security faces considerable danger from DeepFake technology because adversaries can use its capabilities to modify visual media alongside the dissemination of fake information and ...
C&EN

MMPK: A Multimodal Deep Learning Framework to Predict Human Oral Pharmacokinetic Parameters

Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, ...
Frontiers

Next-generation approach to skin disorder prediction employing hybrid deep transfer learning

Introduction: Skin diseases significantly impact individuals' health and mental wellbeing. However, their classification remains challenging due to complex lesion characteristics, overlapping symptoms ...
GitHub

Deep-Learning-Approach-for-Surface-Defect-Detection

A Tensorflow implementation of "Segmentation-Based Deep-Learning Approach for Surface-Defect Detection" The author submitted the paper to Journal of Intelligent ...
Ars Technica

How a stubborn computer scientist accidentally launched the deep learning boom

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...