GLGCN models both global and local features, and extracts global–local motion information. MTCN, on the other hand, takes into account the inconsistency of local limb motion cycles, and facilitates multi-scale temporal convolution to capture the temporal information of limb ...
Interactive attention and improved GCN for continuous sign language recognition 2023, Biomedical Signal Processing and Control Citation Excerpt : It is the primary form of communication between deaf and hearing persons. The research of sign language recognition (SLR) [1–4] helps people and machines ...
In the proposed method, (1) the topological structure information and texture feature of regions of interest (ROIs) are modeled as graphs and processed with graph convolutional network (GCN) to remain the topological features. (2) The local features of ROIs and global features are extracted with...
其中,NxiNix 表示在xx这种edge type下,node ii的邻接节点的集合,XX denotes the set of edge types.说到底,还是和GCN处理异质图的方式没啥区别。我们将L层之后的每一个node的representation称为entity global representation,记做:egloieiglo。 local representation layer: 通过将实体相关的提及表示与多头注意力结合...
The two halves of iCre (19-59 and 60-343) were fused with the constitutively active coiled-coil interaction domain of the yeast transcription factor GCN4 and were inserted at the start codon of the Abhd3 and Ntng2 genes. With this design, the iCre recombines in cells where both Abhd3...
Representation power:相比较与GAT和GCN,high layer时遥遥领先,代表了MaGNet能很好的捕获graph latent representation(从另一个方面也可以说明这点,具有较多layer的GNN通常训练效果很差,因为多层的学习使得Nodes间的信息已经十分smooth,无法捕获有意义的信息。而MaGNet每一层的embeddings全部保留下来做Fusion,因此并没有smooth...
MLC-GCN: Multi-Level Generated Connectome Based GCN for AD Analysis Alzheimer's Disease (AD) is a currently incurable neurodegeneartive disease. Accurately detecting AD, especially in the early stage, represents a high rese... W Zhu,Y Fu,Z Wang 被引量: 0发表: 2024年 A novel multi-step...
Unlike previous models that primarily focus on local feature extraction, we propose a novel collaborative local–global learning model (LOGO) that employs spatio-temporal attention (STA) and graph convolutional networks (GCN). Specifically, LOGO simultaneously extracts hidden traffic features from both ...
Genome-scale metabolic networks (GSMs) are fundamental systems biology representations of a cell’s entire set of stoichiometrically balanced reactions. However, such static GSMs do not incorporate the functional organization of metabolic genes and their
考虑到LiDAR点集固有的拓扑信息,图卷积神经网络(GCNNs)被用于ALS点云分类。为了准确地从山区的ALS数据中提取电力设施,Li等人[34]提出了一个结合局部维度信息和局部几何信息聚合的GCNN。Widyaningrum等人[35]实现了一个动态的GCNN,并将其分类应用从室内点云扩展到室外场景,但性能很差。Wen等人[36]针对任意大小的...