Graph attention neural network for hyperspectral image classification

A novel multi-scale receptive fields graph attention neural network (MRGAT) is proposed for HSI classification in this paper.

Multi-scale receptive fields: : Graph attention neural network for ...

Hyperspectral image (HSI) classification has attracted wide attention in many fields. Applying Graph Neural Network (GNN) to HSI classification is one of ...

Multi-Scale Dense Graph Attention Network for Hyperspectral ...

In recent years, numerous deep learning-based methods have gained increasing attention in hyperspectral classification, particularly the Graph Neural ...

Spectral–Spatial Residual Graph Attention Network for ... - IEEE Xplore

Spectral–Spatial Residual Graph Attention Network for Hyperspectral Image Classification ... Recently, using convolutional neural networks ...

Graph Attention Neural Network for Hyperspectral Image Classification

To overcome the deficiencies, a novel multi-scale receptive fields graph attention neural network (MRGAT) is proposed for HSI classification in ...

Spatial-Pooling-Based Graph Attention U-Net for Hyperspectral ...

In recent years, graph convolutional networks (GCNs) have attracted increasing attention in hyperspectral image (HSI) classification owing to their ...

Hyperspectral Image Classification Based on 3D–2D Hybrid ...

2.4 Graph Attention Network. GAT [36,37,38] is a variant of Graph Neural Network (GNN) and mainly consists of a graph attention layer (GAL) ...

Weighted Feature Fusion of Convolutional Neural Network and ...

Weighted Feature Fusion of Convolutional Neural Network and Graph Attention Network for Hyperspectral Image Classification. Abstract ...

CNN -Enhanced Multi-Scale Graph Attention Network for ...

In recent years, the utilization of both Graph Neural Network (GNN) and Convolutional Neural Network (CNN) in hyperspectral image (HSI) ...

Spectral Pyramid Graph Attention Network for Hyperspectral ... - arXiv

Convolutional neural networks (CNN) have made significant advances in hyperspectral image (HSI) classification. However, standard convolutional ...

Multi-scale receptive fields: Graph attention neural network for...

Hyperspectral image (HSI) classification has attracted wide attention in many fields. Applying Graph Neural Network (GNN) to HSI ...

Hybrid convolutional network with enhanced graph attention ...

Due to their reliance on superficial spectral or spatial information, current hyperspectral image classification techniques frequently fail ...

Spectral Pyramid Graph Attention Network for Hyperspectral Image ...

Convolutional neural networks (CNN) have made significant advances in hyperspectral image (HSI) classification. However, standard convolutional kernel ...

Weighted Feature Fusion of Convolutional Neural Network and ...

... Neural Network and Graph Attention Network for Hyperspectral Image Classification - quanweiliu/WFCG. ... Network for Hyperspectral Image Classification. This ...

Hyperspectral Image Classification Based on Graph Transformer ...

Request PDF | Hyperspectral Image Classification Based on Graph Transformer Network and Graph Attention Mechanism | Graph convolutional networks (GCNs) have ...

Spectral Pyramid Graph Attention Network for Hyperspectral Image ...

Abstract—Convolutional neural networks (CNN) have made significant advances in hyperspectral image (HSI) classification.

Enhancing remote target classification in hyperspectral imaging ...

Graph attention neural network-based remote target classification (GANN-RTC) has been proposed. It has the ability to handle both the labelled and unlabelled ...

Enhancing hyperspectral image classification with graph attention ...

Both convolutional neural networks (CNNs) and graph convolutional networks (GCNs) have demonstrated promising results in HSI classification in recent years.

Spatial-Pooling-Based Graph Attention U-Net for Hyperspectral ...

In recent years, the graph convolutional network (GCN) has attracted increasing attention in hyperspectral image (HSI) classification owing ...

Hyperspectral Image Classification Based on Fusion of ... - MDPI

Convolutional neural networks (CNNs) have attracted significant attention as a commonly used method for hyperspectral image (HSI) classification in recent ...