Dual|Branch Fusion of Convolutional Neural Network and Graph ...

Dual-Branch Fusion of Convolutional Neural Network and Graph ...

Dual-Branch Fusion of Convolutional Neural Network and Graph Convolutional Network for PolSAR Image Classification. Polarimetric synthetic aperture radar ...

Dual Branch Fusion Network for Pathological Image Classification ...

To address these issues, we proposed a two-branch fusion model, named BiFusionNet, which combines CNN and Graph Neural Network (GNN). In the CNN ...

Weighted Feature Fusion of Convolutional Neural Network and ...

Weighted Feature Fusion of Convolutional Neural Network and Graph Attention Network for Hyperspectral Image Classification - quanweiliu/WFCG.

Trunk-Branch Ensemble Convolutional Neural Networks for Video ...

The output feature maps by the trunk network and branch networks are fused by concatenation to form a comprehensive face representation. Furthermore, to enhance ...

ConvFusion A Model for Layer Fusion in Convolutional Neural ...

As such, a neural network can represented as a directional graph G(V, E) with the network layers V as nodes, and directional edges E to indicate ...

TARGCN: temporal attention recurrent graph convolutional neural ...

In this paper, an embedding Emb-GCN layer, a series of gated recurrent units, and a TA layer are proposed to be fused in a network for traffic ...

Dual Fusion-Propagation Graph Neural Network for Multi-View ...

Abstract—Deep multi-view representation learning focuses on training a unified low-dimensional representation for data with multiple sources or modalities.

Enhanced Named Entity Recognition Based on Multi-Feature Fusion ...

is proposed, leveraging dual Graph Neural Networks (GNNs) based on multi-feature fusion. This approach constructs a co-occurrence graph and ...

Primal-Dual Mesh Convolutional Neural Networks - NIPS papers

These meth- ods, however, either consider the input mesh as a graph, and do not exploit specific geometric properties of meshes for feature aggregation and ...

Deep Learning with Graph Convolutional Networks: An Overview ...

Under such a set of wavelet bases, the graph convolutional neural network satisfies locality, and the computational complexity of the graph ...

Heartbeat classification method combining multi-branch ... - Cell Press

... branch convolutional neural networks (CNNs). ... Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional ...

Convolutional neural network - Wikipedia

A convolutional neural network (CNN) is a regularized type of feed-forward neural network that learns features by itself via filter (or kernel) optimization ...

naganandy/graph-based-deep-learning-literature - GitHub

Behavioral Recognition of Skeletal Data Based on Targeted Dual Fusion Strategy ... Double-Branch Multi-Attention based Graph Neural Network for Knowledge Graph ...

A Dual-Branch Dynamic Graph Convolution Based Adaptive ...

A Dual-Branch Dynamic Graph Convolution Based Adaptive TransFormer Feature Fusion Network for EEG Emotion Recognition ... graph convolutional neural networks ...

Hyperspectral Image Classification Based on Fusion ... - Preprints.org

To overcome the above problems, we constructed a network a fusion network based on GCN and CNN, which contains two branches: a graph ...

Learning a Graph Neural Network with Cross Modality Interaction for ...

CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion. ... Multi-focus image fusion with a deep ...

Sign language recognition based on dual-path background erasure ...

... fusion of image and hand landmarks through multi-headed convolutional neural network. ... branch attention based graph and general deep learning ...

Dual-Perception Graph Neural Network for Representation Learning

(2021) propose graph structure learning techniques used for message passing. But most of these methods regard Graph Convolutional Networks (GCN) ...

Graph Neural Networks in Computer Vision

Recent years have seen great success of Convolutional Neural Network (CNN) in ... dual-path neu- ral network with graph convolutional network. This network ...

Full article: A dual-branch multi-feature deep fusion network ...

Convolutional neural network. The CNN has achieved previously unheard-of HSI classification accuracy and efficiency since its debut into the area of remote ...