AZoRobotics on MSN

Combining AI and X-ray physics to overcome tomography data gaps

With PFITRE, Brookhaven scientists achieve breakthrough 3D imaging in nanoscale X-ray tomography, combining AI and physics ...
Tech Xplore

Novel AI method sharpens 3D X-ray vision

X-ray tomography is a powerful tool that enables scientists and engineers to peer inside of objects in 3D, including computer ...
EurekAlert!

AI boosts understanding of ocean dynamics and marine structure safety

Fluid–structure interaction (FSI) governs how flowing water and air interact with marine structures—from wind turbines to ...
EurekAlert!

CornPheno: A game-changer in corn breeding with smartphone-based phenotyping

Corn is one of the world's most important crops, critical for food, feed, and industrial applications. In 2023, corn production in China alone accounted for 41% of total crop production, highlighting ...
IEEE

An Encoder–Decoder Model Based on Spiking Neural Networks for Address Event Representation Object Recognition

Abstract: Address event representation (AER) object recognition task has attracted extensive attention in neuromorphic vision processing. The spike-based and event-driven computation inherent in the ...
INSPIRE

Design and evaluation of a quantum variational graph auto-encoder using quantum graph neural networks

Quantum Variational Graph Auto-Encoders (QVGAE) represent an integration of graph-based machine learning and quantum computing. In this work, we propose a first-of-its-kind quantum implementation of ...
Frontiers

The design of multiple orthogonal signals based on auto-encoder optimization network

As an important part of active sonar, transmitted signals have a great influence on the performance of ocean exploration, however, in the actual environment, due to the existence of the Doppler ...
Frontiers

Convolutional neural networks decode finger movements in motor sequence learning from MEG data

1 Institute of Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia 2 Department of Learning, Data Analytics and Technology, Section Cognition, Data and ...
Scientific Research Publishing

Daniel, G.V., Chandrasekaran, K., Meenakshi, V. and Paneer, P. (2023) Robust Graph Neural-Network-Based Encoder for Node and Edge Deep Anomaly Detection on Attributed Networks ...

ABSTRACT: Drug repositioning aims to identify new therapeutic applications for existing drugs offering a faster and more cost-effective alternative to traditional drug discovery. Since approved drugs ...
marktechpost

How Latent Vector Fields Reveal the Inner Workings of Neural Autoencoders

Neural networks are designed to learn compressed representations of high-dimensional data, and autoencoders (AEs) are a widely-used example of such models. These systems employ an encoder-decoder ...
Scientific Research Publishing

Polyp Segmentation Network with Dual-Decoder Pyramid Visual Converter ()

To address the challenges of morphological irregularity and boundary ambiguity in colorectal polyp image segmentation, we propose a Dual-Decoder Pyramid Vision Transformer Network (DDPVT-Net). This ...