Dual interactive graph convolutional networks for hyperspectral ...

Dual Interactive Graph Convolutional Networks for Hyperspectral ...

In this article, we develop a new dual interactive GCN (DIGCN) which introduces the dual GCN branches to capture spatial information at different scales.

Dual Interactive Graph Convolutional Networks for Hyperspectral ...

Dual Interactive Graph Convolutional Networks for. Hyperspectral Image Classification. Sheng Wan, Shirui Pan, Member, IEEE, Ping Zhong, Senior Member, IEEE ...

[PDF] Dual Interactive Graph Convolutional Networks for ...

Dual Interactive Graph Convolutional Networks for Hyperspectral Image Classification · Sheng Wan, Shirui Pan, +3 authors. Chen Gong · Published in IEEE ...

Dual Interactive Graph Convolutional Networks for Hyperspectral ...

Recently, graph convolutional network (GCN) has progressed significantly and gained increasing attention in hyperspectral image (HSI) classification due to ...

Dual Interactive Graph Convolutional Networks for Hyperspectral ...

Request PDF | Dual Interactive Graph Convolutional Networks for Hyperspectral Image Classification | Recently, graph convolutional network (GCN) has ...

Dual interactive graph convolutional networks for hyperspectral ...

As such, the refined graph information can help enhance the representation power of the model. Furthermore, to avoid the negative effects of the ...

(PDF) Dual Graph Convolutional Network for Hyperspectral Image ...

PDF | Due to powerful feature extraction capability, convolutional neural networks (CNNs) have been widely used for hyperspectral image ...

Dual Interactive Graph Convolutional Networks for Hyperspectral ...

Dual Interactive Graph Convolutional Networks for Hyperspectral Image Classification. Sheng Wan, Shirui Pan, P. Zhong, Xiaojun Chang, Jian Yang, Chen Gong.

Dual Interactive Graph Convolutional Networks for Hyperspectral ...

Dual Interactive Graph Convolutional Networks for Hyperspectral Image Classification. Wan, S., Pan, S., Zhong, P., Chang, X., Yang, J., & Gong, C. IEEE ...

DCG-Net: Enhanced Hyperspectral Image Classification with Dual ...

In recent years, graph convolutional neural networks (GCNs) and convolutional neural networks (CNNs) have made significant strides in hyperspectral image ...

Dual-Coupled CNN-GCN-Based Classification for Hyperspectral ...

Among them, convolutional neural networks (CNN) can extract rich spatial and spectral features from hyperspectral images in a short-range region, whereas graph ...

Two-Branch Deeper Graph Convolutional Network for Hyperspectral ...

“Dual interactive graph convolutional networks for hyperspectral image classification,” IEEE Trans. Geosci. Remote Sens., vol. 60, 2022,. Art. no. 5510214 ...

Graph Convolutional Networks for Hyperspectral Image Classification

Dual Interactive Graph Convolutional Networks for Hyperspectral Image Classification · Environmental Science, Computer Science. IEEE Transactions ...

Discriminative graph convolution networks for hyperspectral image ...

Cited by (12). Dual-graph hierarchical interaction network for referring image segmentation. 2023, Displays.

EGCN: Enhanced Graph Convolutional Network for Hyperspectral ...

Yu, C., Zhou, S., Song, M., Semisupervised hyperspectral band selection based on dual-constrained low-rank representation. IEEE Geoscience ...

Dual Feature Interaction-Based Graph Convolutional Network

Graphs are widely used to model various practical applications. In recent years, graph convolution networks (GCNs) have attracted increasing attention due ...

Spectral Graph Convolutional Network for Hyperspectral Image ...

proposed a multiscale dynamic GCN (MDGCN) [8] and a dual-interactive GCN. (DIGCN) [9] to capture the spatial information at different scales. A ...

Graph Convolutional Networks for Hyperspectral Image Classification

Convolutional neural networks (CNNs) have been attracting increasing attention in hyperspectral (HS) image classification, owing to their ...

Dual Scene Graph Convolutional Network for Motivation Prediction

In each branch, node-oriented and edge-oriented message passing is adopted to propagate interaction information between different nodes and edges. Besides, a ...

Graph Convolutional Network Using Adaptive Neighborhood ... - OUCI

... convolutional layers for hyperspectral image ... Wan, Dual Interactive Graph Convolutional Networks for Hyperspectral Image Classification, IEEE Trans.