Results 61 to 70 of about 5,998 (189)

IntelliMetro‐Hybrid: A Machine Learning and Deep Learning Fusion Model for Economic Optimization in Smart Metro Systems

Transactions on Emerging Telecommunications Technologies, Volume 37, Issue 1, January 2026.
IntelliMetro‐Hybrid is an intelligent fusion framework that integrates machine learning (ML) and deep learning (DL) for real‐time anomaly detection and economic optimization in smart metro systems. The model combines tree‐based feature extraction (Random Forest, XG Boost) with a deep neural classifier to effectively handle imbalanced, heterogeneous ...
Sijin Peng, Yongchang Wei, Zhigang Sun, Yong Chen, Jiang Huang, Hao Chen, Liuyi Chen   +6 more
wiley   +1 more source

Unsupervised Anomaly Detection Based on LLM for Heterogeneous Multivariate Time Series in the Intelligent Computing Center

IET Communications, Volume 20, Issue 1, January/December 2026.
This paper proposes a novel anomaly detection framework for non‐independent and identically distributed (non‐IID) data from heterogeneous devices. First, we introduce a chain of thought metric alignment and ranking mechanism based on a large language model to meet the data heterogeneity challenge.
Xingguo Jiang, Yue Wang, Chunpeng Wu, Xiaohui Wang, Hongyin Chen, Zhenying Tai, Hao Yue, Chang Liu   +7 more
wiley   +1 more source

A Two‐Stage SlowFast‐YE Network for Robust Recognition of Crew Irregularities on the Bridge

IET Intelligent Transport Systems, Volume 20, Issue 1, January/December 2026.
Innovative network structure: Our proposed SlowFast‐YE network is a real‐time, robust two‐stage network designed specifically for identifying various crew irregularities on ship bridges. Key technologies: The incorporation of Softpool and EPSA techniques enhances cross‐scale feature extraction in complex ship bridge scenes.
Deshan Chen, Long Jiang, Liang Fan, Di Zhang   +3 more
wiley   +1 more source

Implicit Hypergraph Neural Network

Accepted at IEEE BigData ...
Choudhuri, Akash, Zhong, Yongjian, Adhikari, Bijaya   +2 more
openaire   +2 more sources

A Hybrid Deep Learning Framework for Early Detection of Ovarian Cancer Using Ultrasound and MRI Images on a Secure Cloud Platform

Complexity, Volume 2026, Issue 1, 2026.
Ovarian cancer continues to pose a major diagnostic challenge, as early‐stage disease often presents with subtle and heterogeneous imaging characteristics that limit the effectiveness of single‐modality analysis. In response to this challenge, this study proposes a novel hybrid deep learning framework for the early detection and classification of ...
Umesh Kumar Lilhore, Vanusha D., Srilatha Gundapaneni, Anto Lourdu Xavier Raj Arockia Selvarathinam, Rasmi A., Sarita Simaiya, Lidia Gosy Tekeste, Ehab Seif Ghith, Heba G. Mohamed, Raul Alcaraz Martinez   +9 more
wiley   +1 more source

Preventing Over-Smoothing for Hypergraph Neural Networks

, 2022
In recent years, hypergraph learning has attracted great attention due to its capacity in representing complex and high-order relationships. However, current neural network approaches designed for hypergraphs are mostly shallow, thus limiting their ability to extract information from high-order neighbors.
Chen, Guanzi, Zhang, Jiying, Xiao, Xi, Li, Yang   +3 more
openaire   +2 more sources

Bi-View Contrastive Learning with Hypergraph for Enhanced Session-Based Recommendation

Information
Session-based recommendation (SBR) aims to predict a user’s next interests based on their actions in a single visit. Recent methods utilize graph neural networks to study the pairwise relationship of item transfers, yet these often overlook the complex ...
Zijun Wang, Lai Wei
doaj   +1 more source

How Does Reverse‐Conformity Ambivalent Psychology Influence Rumor Spreading?

Discrete Dynamics in Nature and Society, Volume 2026, Issue 1, 2026.
In the age of social media, rumor dissemination brings serious negative impacts to society. It is important to explore the dissemination mechanism and management strategies to control rumor dissemination and reduce negative impacts. Considering the effect of reverse‐conformity ambivalent psychology on the rumor dissemination process, a novel dynamic ...
Jiaqi Zhang, Yanyuan Su, Zhengxin Yan, Yaming Zhang, Ahmed Ezzat Matouk   +4 more
wiley   +1 more source

Learning from networked examples [PDF]

, 2017
Many machine learning algorithms are based on the assumption that training examples are drawn independently. However, this assumption does not hold anymore when learning from a networked sample because two or more training examples may share some common ...
Guo, Zheng-Chu, Ramon, Jan, Wang, Yuyi
core   +2 more sources

Multiview Hypergraph Fusion Network for Change Detection in High-Resolution Remote Sensing Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Currently, convolutional neural networks and transformers have been the dominant paradigms for change detection (CD) thanks to their powerful local and global feature extraction capabilities. However, with the improvement of resolution, spatial, spectral,
Xue Zhao, Kai Zhang, Feng Zhang, Jiande Sun, Wenbo Wan, Huaxiang Zhang   +5 more
doaj   +1 more source