Results 161 to 170 of about 13,207 (236)

Attribute knowledge and KBGAT for predicting the accuracy of the harmonized system code for classifying import and export commodities. [PDF]

Sci Rep
Qi L, Zhang Q, Lin X, Zhang J, Liao M.
europepmc   +1 more source

Integrating Artificial Intelligence With Droplet‐Based Microfluidics: Advances, Challenges, and Emerging Opportunities

Advanced Intelligent Systems, EarlyView.
Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai, Sukrit Gaira, Rongfeng Wang, Qingtian Zhang, Ming Li, Liao Wu, Diangeng Li, Yi Li, Chengchen Zhang, Jinhong Guo, Shi‐Yang Tang   +10 more
wiley   +1 more source

Enhancing Atomic‐Resolution in Electron Microscopy: A Deep Learning Denoiser Operating in the Frequency Domain

Advanced Intelligent Systems, EarlyView.
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, Marc Botifoll, Xuli Chen, Martin Børstad Eriksen, Jing Yu, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Jordi Arbiol   +8 more
wiley   +1 more source

Deep learning assisted LDPC decoding for 5G IoT networks in fading environments. [PDF]

Sci Rep
Tera SP, Chinthaginjala R, Al-Turjman F, Ahmad S.   +3 more
europepmc   +1 more source

Upsampling DINOv2 Features for Unsupervised Vision Tasks and Weakly Supervised Materials Segmentation

Advanced Intelligent Systems, EarlyView.
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, Antonis Vamvakeros, Samuel J. Cooper   +2 more
wiley   +1 more source

Prediction of the ectasia screening index from raw Casia2 volume data for keratoconus identification by using convolutional neural networks. [PDF]

PLoS One
Mirsalehi M, Fassbind B, Streich A, Langenbucher A.   +3 more
europepmc   +1 more source

GraphNeuralCloth: A Graph‐Neural‐Network‐Based Framework for Non‐Skinning Cloth Simulation

Advanced Intelligent Systems, EarlyView.
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, Xiaomei Wang, Xiaoqi Song, Chenchen Fan, Bohao Zhu, Jianan Peng, Qixin Liang, James Lam, Kam‐Yim Sze, Ka‐Wai Kwok   +9 more
wiley   +1 more source

A deep dictionary clustering approach for unsupervised image retrieval using convolutional sparse coding. [PDF]

Sci Rep
Sucharitha G, Vikas B, Reddy PVB, Suneel S, Divya N, Osman O, Rasheed J.   +6 more
europepmc   +1 more source

Building an Intelligent Cardiovascular System Platform: Embedding Artificial Intelligence across All Facets of Cardiovascular Medicine

Advanced Intelligent Systems, EarlyView.
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, Xingwei Zhao, Qiuting Li, Yang Yu, Chunxiang Zhang   +4 more
wiley   +1 more source

Primary care prediction of hip and knee replacement 1-5 years in advance using Temporal Graph-based Convolutional Neural Networks (TG-CNNs). [PDF]

Rheumatology (Oxford)
Hancox Z, Kingsbury SR, Conaghan PG, Clegg A, Relton SD.   +4 more
europepmc   +1 more source