Rail Vision: Quantum Transportation Delivers First Transformer-Based Neural Decoder for Universal Quantum Error Correction

Achieves superior decoding accuracy and dramatically improved efficiency compared to leading classical algorithmsRa’anana, Israel, Jan. 15, 2026 ...
Morning Overview on MSN

Different AI models are converging on how they encode reality

Artificial intelligence systems that look nothing alike on the surface are starting to behave as if they share a common ...
Beebom

What is CNN in Deep Learning? The AI Behind Computer Vision

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...
Frontiers

Detection of leptomeningeal angiomas in brain MRI of Sturge-Weber syndrome using multi-scale multi-scan Mamba

Objectives: Sturge-Weber syndrome (SWS) is a congenital neurological disorder occurring in the early childhood. Timely diagnosis of SWS is essential for proper medical intervention that prevents the ...
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 ...
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 ...
IEEE

SVInvNet: A Densely Connected Encoder-Decoder Architecture for Seismic Velocity Inversion

Abstract: This study presents a deep learning (DL)-based approach to the seismic velocity inversion problem, focusing on both noisy and noiseless training datasets of varying sizes. Our seismic ...
IEEE

An Encoder-Decoder Deep Learning Approach for Multistep Service Traffic Prediction

Abstract: The prediction of traffic in regards to data services can be leveraged by cloud and edge computing orchestration mechanisms in order to minimize the costly number of resources being utilized ...