Results 41 to 50 of about 1,216 (173)

Preventing Over-Smoothing for Hypergraph Neural Networks

CoRR, 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

Promises and limitations of deep learning for predicting knee osteoarthritis progression from medical imaging: A systematic review

Knee Surgery, Sports Traumatology, Arthroscopy, EarlyView.
Abstract Purpose To systematically evaluate the performance, methodological quality, and translational barriers of deep learning (DL) models for predicting knee osteoarthritis (KOA) progression from medical imaging. Methods Following PRISMA guidelines, we searched PubMed, Scopus, and Web of Science (inception to June 2026) for peer‐reviewed studies ...
Amna Gillani, Rüdiger von Eisenhart‐Rothe, Klaus Woertler, Michael T. Hirschmann, Daniel Rueckert, Florian Hinterwimmer   +5 more
wiley   +1 more source

Land Use and Land Cover Analysis for Solid Waste Management in NCT Delhi Using Fusion Aware Segformer

Land Degradation &Development, EarlyView.
ABSTRACT The use of Land Use Land Cover (LULC) analysis is a fundamental requirement for urban solid waste management (SWM); however, conventional LULC analysis methods are not well suited to the spatio‐temporal variability, multi‐sensor heterogeneity, and seasonal variations of highly dynamic urban environments.
Rubeena Vohra, Ashish Kumar
wiley   +1 more source

A Novel Full‐Chain Loop Tracking Auditing Framework for Obtaining Audit Evidence With Reasonable Assurance

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT As an attestation engagement, auditing is required to provide reasonable assurance for its conclusions. Traditional auditing has limited capacity to handle unstructured data and is usually based on audit sampling techniques, which can lead to the neglect of important audit evidence during the auditing process and result in a higher audit risk,
Xiaojia Wang, Ziqing Luo, Chaoxu Mu
wiley   +1 more source

Deep Learning-Based Community Detection Approach on Multimedia Social Networks

Applied Sciences, 2021
Exploiting multimedia data to analyze social networks has recently become one the most challenging issues for Social Network Analysis (SNA), leading to defining Multimedia Social Networks (MSNs).
Antonino Ferraro, Vincenzo Moscato, Giancarlo Sperlì   +2 more
doaj   +1 more source

H2CD: Semantic‐Enhanced Heterogeneous Hypergraph Network With Large Language Model for Cognitive Diagnosis

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Cognitive diagnosis aims to infer learners' knowledge states from their exercise responses, enabling personalised education at scale. Existing methods represent exercises solely by coarse‐grained knowledge component annotations, overlooking semantic content and step‐level cognitive processes.
Youheng Bai, Zitao Liu, Mingliang Hou, Teng Guo, Weiqi Luo   +4 more
wiley   +1 more source

Single‐cell marker gene clustering: A unified deep learning framework for marker gene‐based clustering of single‐cell RNA‐sequencing data

Quantitative Biology, Volume 14, Issue 3, September 2026.
Abstract Single‐cell RNA sequencing (scRNA‐seq) has transformed the study of cellular heterogeneity by making it possible to classify individual cells and their functional states. However, the analysis remains difficult because high dropout rates lead to sparse and noisy expression data.
Shahriar Rahman Niloy, Toushif Muktashid Hasan, Md. Saiduzzaman Apu, Fahim Hafiz, Salekul Islam, Riasat Azim   +5 more
wiley   +1 more source

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

Link Prediction Method Based on Hypergraph Neural Network [PDF]

Jisuanji gongcheng
With the rapid development of information technology, link prediction has been widely applied in various fields. Current link prediction methods are based on subgraph extraction.
CHEN Liang, ZHAO Ying, SHI Shenghui, YIN Ling
doaj   +1 more source

GBT‐SAM: A Parameter‐Efficient Depth‐Aware Model for Generalizable Brain Tumor Segmentation on mp‐MRI

International Journal of Imaging Systems and Technology, Volume 36, Issue 4, July 2026.
ABSTRACT Gliomas are aggressive brain tumors that require accurate imaging‐based diagnosis, where automated segmentation plays a central role in assessing tumor morphology and guiding treatment decisions. Manual delineation of gliomas is time‐consuming and prone to variability, motivating the use of deep learning to improve consistency and alleviate ...
Cecilia Diana‐Albelda, Roberto Alcover‐Couso, Álvaro García‐Martín, Jesus Bescos, Marcos Escudero‐Viñolo   +4 more
wiley   +1 more source