Two-Stage Attention Network for hyperspectral image classification-Reference-Cited by-同舟云学术

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Two-Stage Attention Network for hyperspectral image classification

Published:2021-11-06 Issue:24 Volume:42 Page:9249-9284
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Wu Peida¹^ORCID,Cui Ziguan¹^ORCID,Gan Zongliang¹,Liu Feng¹

Affiliation:

1. College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China

Funder

National Natural Science Foundation of China

‘1311 Talent Program’ of Nanjing University of Posts and Telecommunications

Research Fund of Nanjing University of Posts and Telecommunications

“1311 Talent Program” of Nanjing University of Posts and Telecommunications

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2021.1993464

Reference57 articles.

1. SSDC-DenseNet: A Cost-Effective End-to-End Spectral-Spatial Dual-Channel Dense Network for Hyperspectral Image Classification

2. Hyperspectral Data Analysis for Arid Vegetation Species : Smart & Sustainable Growth

3. Support vector machines, import vector machines and relevance vector machines for hyperspectral classification — A comparison

4. BS-Nets: An End-to-End Framework for Band Selection of Hyperspectral Image

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Discriminating Spectral–Spatial Feature Extraction for Hyperspectral Image Classification: A Review;Sensors;2024-05-08

2. TBTA-D2Net: a novel hyperspectral image classification method based on triple-branch ternary-attention mechanism and Dense2Net;International Journal of Remote Sensing;2023-11-17

3. Segmentation-based linear discriminant analysis with information theoretic feature selection for hyperspectral image classification;International Journal of Remote Sensing;2023-06-03

4. H-RNet: Hybrid Relation Network for Few-Shot Learning-Based Hyperspectral Image Classification;Remote Sensing;2023-05-09

5. DRs-UNet: A Deep Semantic Segmentation Network for the Recognition of Active Landslides from InSAR Imagery in the Three Rivers Region of the Qinghai–Tibet Plateau;Remote Sensing;2022-04-12

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