Hyper-ES2T: Efficient Spatial–Spectral Transformer for the classification of hyperspectral remote sensing images

Hyper-ES2T: Efficient Spatial–Spectral Transformer for the classification of hyperspectral remote sensing images

In recent years, convolutional neural networks have continuously dominated the downstream tasks on hyperspectral remote sensing images with its strong local feature extraction capability. However, convolution operations cannot effectively capture the long-range dependencies and repeatedly stacking c...

Full description

Bibliographic Details
Main Authors: Wenxuan Wang, Leiming Liu, Tianxiang Zhang, Jiachen Shen, Jing Wang, Jiangyun Li
Format: Article
Language:English
Published: Elsevier 2022-09-01
Series:International Journal of Applied Earth Observations and Geoinformation
Subjects:
Deep learning
Hyperspectral image classification
Remote sensing
Spatial–spectral Transformer
Feature enhancement
Bilateral classification network
Online Access:http://www.sciencedirect.com/science/article/pii/S1569843222001935

Internet

http://www.sciencedirect.com/science/article/pii/S1569843222001935

Similar Items