Tech Xplore

Holographic storage approach packs more data into the same space by encoding three properties of light

Researchers have developed a holographic data storage approach that stores and retrieves information in three dimensions by ...
Scientific Research Publishing

A Spatio-Temporal Prediction Model for Wall Turbulence Based on Hybrid Neural Networks ()

The spatio-temporal evolution of wall-bounded turbulence is characterized by high nonlinearity, multi-scale dynamics, and chaotic nature, making its accurate prediction a significant challenge for ...
The Malaysian Reserve

NetAirus Technologies Launches Panatem™ an Industry-First World-Model Artificial Intelligence Framework for Augmented Reality Headsets

SAN DIEGO, March 12, 2026 /PRNewswire/ — NetAirus Technologies – NetAirus introduces Panatem™ an Artificial Intelligence World Model framework that enables next-gen AR/VR and smart glasses to ...
Machine Design

Reduce Encoder Cost While Gaining Functionality with 44-Turn Sensors

How to substantially reduce encoder cost while gaining functionality with 44-Turn multi-turn rotary position sensors—retaining count and position during power loss. New technology reduces encoder ...
Scientific Research Publishing

Chen, H., Zhang, Y., Kalra, M.K., Lin, F., Chen, Y., Liao, P., et al. (2017) Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network. IEEE Transactions on ...

ABSTRACT: Magnetic Resonance Imaging (MRI) is commonly applied to clinical diagnostics owing to its high soft-tissue contrast and lack of invasiveness. However, its sensitivity to noise, attributable ...
IEEE

Deep Learning-Based Iterative Residual Encoder-Decoder Solution for Electromagnetic Modeling over a Broad Frequency Band

Abstract: In this letter, we propose a deep learning-based iterative residual encoder-decoder method (IRED), which provides an efficient deep learning framework for electromagnetic modeling over a ...
ahajournals.org

Abstract P3089: Predicting Reductions In Hemoglobin A1c From Large Dietary Datasets Using Artificial Intelligence Pipeline With Interpretable Encoder-Decoder Deep Neural Networks

Introduction: Artificial intelligence algorithms can help understand and predict the complex interactions between dietary intake and health outcomes, especially from large datasets. Precision ...