Results 251 to 260 of about 5,879,357 (336)

Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing

Advanced Intelligent Systems, EarlyView.
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian, Liuchao Jin, Qi Ge, Wei‐Hsin Liao, Andrés Díaz Lantada, Francisco Franco Martínez, Tianyu Zhang, Tao Liu, Charlie C. L. Wang, Mohammad Hossein Mosallanejad, Reza Ghanavati, Abdollah Saboori, Alejandro De Blas De Miguel, William Solórzano‐Requejo, Yi Cai, Xiangyang Dong, Huangyi Qu, Najmeh Samadiani, Guangyan Huang, Austin Downey, Yanzhou Fu, Lang Yuan, Tsz‐Kwan (Glory) Lee, Arbind Agrahari Baniya, Eisha Waseem, Abdul Rahman Sani, Abbas Z. Kouzani, Yijia Wu, Markus P. Nemitz, Masoud Shirzad, Dageon Oh, Seung Yun Nam, Amedeo Franco Bonatti, Irene Chiesa, Gabriele Maria Fortunato, Giovanni Vozzi, Carmelo De Maria, Mahdi Bodaghi   +37 more
wiley   +1 more source

Unsupervised Learning of Effective Quantum Impurity Models [PDF]

Jonas B. Rigo, Andrew K. Mitchell
openalex   +1 more source

Multitarget Recognition of Flower Images Based on Lightweight Deep Neural Network and Transfer Learning

Advanced Intelligent Systems, EarlyView.
This article proposes a lightweight YOLOv4‐based detection model using MobileNetV3 or CSPDarknet53_tiny, achieving 30+ FPS and higher mAP. It also presents a ShuffleNet‐based classification model with transfer learning and GAN‐augmented images, improving generalization and accuracy.
Qingyang Liu, Yanrong Hu, Hongjiu Liu
wiley   +1 more source

Unsupervised learning using EHR and census data to identify distinct subphenotypes of newly diagnosed hypertension patients. [PDF]

PLoS One
Hall JM, Xu J, Walsh MG, Cho HD, Harrell G, Keshwani SA, Smith SM, Staras SAS.   +7 more
europepmc   +1 more source

HC-GLAD: Dual Hyperbolic Contrastive Learning for Unsupervised Graph-Level Anomaly Detection [PDF]

Yali Fu, Jindong Li, Jiahong Liu, Qianli Xing, Yanyan Wang, Irwin King   +5 more
openalex   +1 more source

From Droplet to Diagnosis: Spatio‐Temporal Pattern Recognition in Drying Biofluids

Advanced Intelligent Systems, EarlyView.
This article integrates machine learning (ML) with the spatio‐temporal evolution of biofluid droplets to reveal how drying and self‐assembly encode distinctive compositional fingerprints. By leveraging textural features and interpretable ML, it achieves robust classification of blood abnormalities with over 95% accuracy.
Anusuya Pal, Amalesh Gope, Miho Yanagisawa   +2 more
wiley   +1 more source

Unlocking the soundscape of coral reefs with artificial intelligence: pretrained networks and unsupervised learning win out. [PDF]

PLoS Comput Biol
Williams B, Balvanera SM, Sethi SS, Lamont TAC, Jompa J, Prasetya M, Richardson L, Chapuis L, Weschke E, Hoey A, Beldade R, Mills SC, Haguenauer A, Zuberer F, Simpson SD, Curnick D, Jones KE.   +16 more
europepmc   +1 more source

Cross‐Modal Characterization of Thin‐Film MoS2 Using Generative Models

Advanced Intelligent Systems, EarlyView.
Cross‐modal learning is evaluated using atomic force microscopy (AFM), Raman spectroscopy, and photoluminescence spectroscopy (PL) through unsupervised learning, regression, and autoencoder models. Autoencoder models are used to generate spectroscopy data from the microscopy images.
Isaiah A. Moses, Chen Chen, Joan M. Redwing, Wesley F. Reinhart   +3 more
wiley   +1 more source

Cross-device federated unsupervised learning for the detection of anomalies in single-lead electrocardiogram signals. [PDF]

PLOS Digit Health
Kapsecker M, Jonas SM.
europepmc   +1 more source

gnSPADE: Incorporating Gene Network Structures Enhances Reference‐Free Deconvolution in Spatial Transcriptomics

Advanced Intelligent Systems, EarlyView.
gnSPADE integrates gene‐network structures into a probabilistic topic modeling framework to achieve reference‐free cell‐type deconvolution in spatial transcriptomics. By embedding gene connectivity within the generative process, gnSPADE enhances biological interpretability and accuracy across simulated and real datasets, revealing spatial organization ...
Aoqi Xie, Yuehua Cui
wiley   +1 more source