Graph Guided Transformer: An Image-Based Global Learning Framework for Hyperspectral Image Classification-Reference-Cited by-同舟云学术

Graph Guided Transformer: An Image-Based Global Learning Framework for Hyperspectral Image Classification

Published:2023 Issue: Volume:20 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Shi Chengzhong¹,Liao Qiming¹,Li Xinping¹^ORCID,Zhao Lin¹^ORCID,Li Wen²

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

2. Hunan Institute of Science and Technology, Yueyang, China

Funder

Natural Science Foundation of Hunan Province of China

Scientific Research Project of Education Department of Hunan Province

Undergraduate Training and Innovation Project of Hunan Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/10034981/10261261.pdf?arnumber=10261261

Reference17 articles.

1. Superpixel Sampling Networks

2. Locally linear discriminant analysis for multimodally distributed classes for face recognition with a single model image

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

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

5. Transformer for graphs: An overview from architecture perspective;min;arXiv 2202 08455,2022

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