Review of Image Classification Algorithms Based on Graph Convolutional Networks
W Tang - EAI Endorsed Transactions on AI and Robotics, 2023 - publications.eai.eu
In recent years, graph convolutional networks (GCNs) have gained widespread attention
and applications in image classification tasks. While traditional convolutional neural …
and applications in image classification tasks. While traditional convolutional neural …
A unified framework of graph structure learning, graph generation and classification for brain network analysis
Recently, functional brain networks have been employed for classifying neurological
disorders, such as autism spectrum disorders (ASDs). Graph convolutional networks (GCNs) …
disorders, such as autism spectrum disorders (ASDs). Graph convolutional networks (GCNs) …
脑网络分析方法及其应用.
黄嘉爽， 接标， 丁卫平， 张道强 - … & Processing/Shu Ju Cai Ji …, 2021 - search.ebscohost.com
网络结构作为一种常见的数据关系表示方法被大量运用在各类研究中. 人的大脑也可通过定义
节点和连接边的方式抽象成一个复杂的网络结构. 这个网络通常被简称为脑网络 …
节点和连接边的方式抽象成一个复杂的网络结构. 这个网络通常被简称为脑网络 …
[HTML][HTML] Fusing Multiview Functional Brain Networks by Joint Embedding for Brain Disease Identification
Background: Functional brain networks (FBNs) derived from resting-state functional MRI (rs-
fMRI) have shown great potential in identifying brain disorders, such as autistic spectrum …
fMRI) have shown great potential in identifying brain disorders, such as autistic spectrum …
[HTML][HTML] TITAN: Combining a bidirectional forwarding graph and GCN to detect saturation attack targeted at SDN
L Ran, Y Cui, J Zhao, H Yang - Plos one, 2024 - journals.plos.org
The decoupling of control and forwarding layers brings Software-Defined Networking (SDN)
the network programmability and global control capability, but it also poses SDN security …
the network programmability and global control capability, but it also poses SDN security …
A stepwise multivariate Granger causality method for constructing hierarchical directed brain functional network
Q Gao, N Luo, M Liang, W Zhou, Y Li… - … on Neural Networks …, 2022 - ieeexplore.ieee.org
The directed brain functional network construction gives us the new insights into the
relationships between brain regions from the causality point of view. The Granger causality …
relationships between brain regions from the causality point of view. The Granger causality …
Cost-Sensitive Weighted Contrastive Learning Based on Graph Convolutional Networks for Imbalanced Alzheimer's Disease Staging
Identifying the progression stages of Alzheimer's disease (AD) can be considered as an
imbalanced multi-class classification problem in machine learning. It is challenging due to …
imbalanced multi-class classification problem in machine learning. It is challenging due to …
[HTML][HTML] Hierarchical graph learning with convolutional network for brain disease prediction
T Liu, F Liu, Y Wan, R Hu, Y Zhu, L Li - Multimedia Tools and Applications, 2024 - Springer
In computer-aided diagnostic systems, the functional connectome approach has become a
common method for detecting neurological disorders. However, the existing methods either …
common method for detecting neurological disorders. However, the existing methods either …
Biomarker Investigation using Multiple Brain Measures from MRI through XAI in Alzheimer's Disease Classification
Alzheimer's Disease (AD) is the world leading cause of dementia, a progressively impairing
condition leading to high hospitalization rates and mortality. To optimize the diagnostic …
condition leading to high hospitalization rates and mortality. To optimize the diagnostic …
Component importance preference-based evolutionary graph neural architecture search
Y Liu, J Liu, Y Teng - Information Sciences, 2024 - Elsevier
Recently, graph neural architecture search (GNAS) has become an increasingly hot
research topic as a promising technique for automatically searching graph neural networks …
research topic as a promising technique for automatically searching graph neural networks …