When Multigranularity Meets Spatial–Spectral Attention: A Hybrid Transformer for Hyperspectral Image Classification-Reference-Cited by-同舟云学术

When Multigranularity Meets Spatial–Spectral Attention: A Hybrid Transformer for Hyperspectral Image Classification

Published:2023 Issue: Volume:61 Page:1-18
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Ouyang Er¹^ORCID,Li Bin¹^ORCID,Hu Wenjing¹,Zhang Guoyun¹^ORCID,Zhao Lin¹^ORCID,Wu Jianhui¹^ORCID

Affiliation:

1. Hunan Engineering Technology Research Center for 3D Reconstruction and Intelligent Application, School of Information Science and Engineering, Hunan Institute of Science and Technology, Yueyang, China

Funder

Natural Science Foundation of Hunan Province of China

Scientific Research Fund of the Hunan Provincial Education Department

Graduate Research and Innovation Project of Hunan Province

Graduate Research and Innovation Project of Hunan Institute of Science and Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10038735.pdf?arnumber=10038735

Reference50 articles.

1. Hyperspectral Image Classification Using Mixed Convolutions and Covariance Pooling

2. HybridSN: Exploring 3-D–2-D CNN Feature Hierarchy for Hyperspectral Image Classification

3. Physically Constrained Transfer Learning Through Shared Abundance Space for Hyperspectral Image Classification

4. Hyperspectral Image Classification With Contrastive Self-Supervised Learning Under Limited Labeled Samples

5. 3-D Deep Learning Approach for Remote Sensing Image Classification

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