Results 161 to 170 of about 43,821 (259)
The newly developed AI‐automated Fast Fourier Transform denoising algorithm surpasses conventional real‐space methods by revealing even light atoms otherwise hidden in noisy backgrounds. Atomic resolution electron microscopy has become an essential tool for many scientific fields, when direct visualization of atomic arrangements and defects is needed ...
Ivan Pinto‐Huguet +8 more
wiley +1 more source
Innovative application of a traffic-prediction spatio-temporal graph convolutional network for dengue disease forecasting. [PDF]
Siabi N +4 more
europepmc +1 more source
Feature from recent image foundation models (DINOv2) are useful for vision tasks (segmentation, object localization) with little or no human input. Once upsampled, they can be used for weakly supervised micrograph segmentation, achieving strong results when compared to classical features (blurs, edge detection) across a range of material systems.
Ronan Docherty +2 more
wiley +1 more source
A Novel PTS Technique with Side Information Blind Detector Based on Minimized Error Accumulation for PAPR Reduction in Coded Underwater Acoustic OFDM Systems. [PDF]
Xing S, Wei B, Yu Y, Bai Y, Yin J.
europepmc +1 more source
GraphNeuralCloth: A Graph‐Neural‐Network‐Based Framework for Non‐Skinning Cloth Simulation
This study presents a cloth motion capture system and a point‐cloud‐to‐mesh processing method to support the prediction of real‐world fabric deformation. GraphNeuralCloth, a graph neural‐network (GNN)‐based framework is also proposed to estimate the cloth morphology change in real time.
Yingqi Li +9 more
wiley +1 more source
Acute deep neck infection MRI: deep learning segmentation and clinical relevance of retropharyngeal edema volume. [PDF]
Viertonen VS +6 more
europepmc +1 more source
This paper presents an integrated AI‐driven cardiovascular platform unifying multimodal data, predictive analytics, and real‐time monitoring. It demonstrates how artificial intelligence—from deep learning to federated learning—enables early diagnosis, precision treatment, and personalized rehabilitation across the full disease lifecycle, promoting a ...
Mowei Kong +4 more
wiley +1 more source
From Capture-Recapture to No Recapture: Efficient SCAD Even After Software Updates. [PDF]
Vedros KA +3 more
europepmc +1 more source
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
Accelerating Catalyst Materials Discovery With Large Artificial Intelligence Models
AI‐empowered catalysis research via integrated database platform, universal machine learning interatomic potentials (MLIPs), and large language models (LLMs). ABSTRACT The integration of artificial intelligence (AI) into catalysis is fundamentally reshaping the research paradigm of catalyst discovery.
Di Zhang +7 more
wiley +2 more sources

