Results 131 to 140 of about 5,438,478 (196)

Beauty in the Eye of AI: Aligning LLMs and Vision Models with Human Aesthetics in Network Visualization

Computer Graphics Forum, EarlyView.
Abstract Network visualization has traditionally relied on heuristic metrics, such as stress, under the assumption that optimizing them leads to aesthetic and informative layouts. However, no single metric consistently produces the most effective results.
X. Li, P. Zhang, X. Wang, H. Shen, Y. Hu
wiley   +1 more source

Machine learning approaches in automated infant General Movements Assessment: A scoping review

Developmental Medicine &Child Neurology, EarlyView.
Automated infant General Movements Assessment increasingly uses machine‐ and deep‐learning approaches to classify movement patterns and estimate cerebral palsy risk from video or sensor data. This scoping review highlights how dataset characteristics, recording environment, pose‐estimation accuracy, feature extraction, and model design influence system
Manpreet Kaur, Hamid Abbasi, Sîan A. Williams, Thor F. Besier, Angus J. C. McMorland   +4 more
wiley   +1 more source

MF-GCN: Multimodal Information Fusion Using Incremental Graph Convolutional Network for Ship Behavior Anomaly Detection

Ship behavior anomaly detection is critical for intelligent perception and early warning in complex inland waterways, where single-source sensing (e.g., AIS-only or vision-only) is often fragile under occlusion, illumination variation, and signal noise ...
Weizhi Nie, Hao Wen, Aoxiang Liu, Naiming Ge, Jinhao Zhang, Ruixin Ma   +5 more
core   +1 more source

GCN-TC: Combining Trace Graph with Statistical Features for Network Traffic Classification

, 2019
For machine-learning-based network traffic classification, we usually need large number of correctly labeled samples (ground truth) for model-training to get high accuracy.
Jingwei Zheng, Zheng, Jingwei, Dagang Li, Li, Dagang   +3 more
core   +1 more source

Artificial Intelligence in Neonatal Care: The Breadth of Promise, the Depth of Challenge—An Overview

Journal of Paediatrics and Child Health, EarlyView.
ABSTRACT Artificial intelligence (AI) is becoming an integral tool in clinical care. The recent position statement by the Royal Australasian College of Physicians (RACP) provides a timely practical blueprint on implementing and monitoring the use of AI in clinical practice.
N. M. Lai, K. T. Yeo, J. Y. Kong, M. E. Abdel‐Latif   +3 more
wiley   +1 more source

Geno-GCN: A Genome-specific Graph Convolutional Network for Diabetes Prediction

Drawing inspiration from convolutional neural networks graph convolutional networks GCNs have been implemented in various applications Yet the integration of GCNs into clinical settings particularly in the context of complex health conditions like ...
Zhang, G, Lin, H, Lu, J, Guo, K, Grosser, M   +4 more
core   +1 more source

Microbiome and Metabolomics in Obesity: Advances in Understanding and Interventions Across the Lifespan

Obesity Reviews, EarlyView.
ABSTRACT Obesity arises from intertwined and reciprocal diet‐microbiome‐host pathways that reshape energy balance, insulin sensitivity, and inflammation. This review synthesizes mechanistic links between microbial functions and metabolic control, charts lifestyle‐related lifecourse dynamics from birth to older age, examines how GLP‐1‐based therapies ...
Ioanna Panagiota Kalafati, David Krongauz, Alice Bosco, Antonio Noto, Cristina Piras, Maria Kafyra, Angelica Dessì, Matteo Mauri, Luigi Atzori, Adina Weinberger, Vassilios Fanos, George V. Dedoussis, on behalf of the BETTER4U consortium   +12 more
wiley   +1 more source

Guest Editorial: Graph Representation Learning for Feature Extraction and Signal Processing

CAAI Transactions on Intelligence Technology, EarlyView.
Xin Ning
wiley   +1 more source

Combining Voiceprint Feature Extraction With Deep Learning Based Classifiers for Early Chronic Obstructive Pulmonary Disease Screening

Vector: The Journal of Engineering, Volume 2027, Issue 1, January/December 2027.
Graphic Abstract (GA) presents an overview of the CNN‐based classification process, which consists of several convolutional layers, several pooling layers, and a classification layer. Multilayer CNNs are capable of automatic feature enhancement, denoising, feature extraction, and pattern recognition tasks, and they have been applied in automatic ...
Pi‐Yun Chen, Can‐Xiang Wang, Neng‐Sheng Pai, Yu‐En Cheng, Chun‐Yu Lin, Chien‐Ming Li, Chia‐Hung Lin   +6 more
wiley   +1 more source

Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting

, 2020
Modeling complex spatial and temporal correlations in the correlated time series data is indispensable for understanding the traffic dynamics and predicting the future status of an evolving traffic system.
Bai, Lei, Wang, Can, Yao, Lina, Wang, Xianzhi, Li, Can   +4 more
core