Multiscale Pixel-Level and Superpixel-Level Method for Hyperspectral Image Classification: Adaptive Attention and Parallel Multi-Hop Graph Convolution

Multiscale Pixel-Level and Superpixel-Level Method for Hyperspectral Image Classification: Adaptive Attention and Parallel Multi-Hop Graph Convolution

Convolutional neural networks (CNNs) and graph convolutional networks (GCNs) have led to promising advancements in hyperspectral image (HSI) classification; however, traditional CNNs with fixed square convolution kernels are insufficiently flexible to handle irregular structures. Similarly, GCNs tha...

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Bibliographic Details
Main Authors: Junru Yin, Xuan Liu, Ruixia Hou, Qiqiang Chen, Wei Huang, Aiguang Li, Peng Wang
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Remote Sensing
Subjects:
convolutional neural networks (CNNs)
graph convolutional networks (GCNs)
hyperspectral image (HSI) classification
attention mechanism
multi-scale features
Online Access:https://www.mdpi.com/2072-4292/15/17/4235

Internet

https://www.mdpi.com/2072-4292/15/17/4235

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