Reinforcement Learning Based Markov Edge Decoupled Fusion Network for Fusion Classification of Hyperspectral and LiDAR-Reference-Cited by-同舟云学术

Reinforcement Learning Based Markov Edge Decoupled Fusion Network for Fusion Classification of Hyperspectral and LiDAR

Published:2024 Issue: Volume:26 Page:7174-7187
ISSN:1520-9210
Container-title:IEEE Transactions on Multimedia
language:
Short-container-title:IEEE Trans. Multimedia

Author:

Wang Haoyu¹^ORCID,Cheng Yuhu¹^ORCID,Liu Xiaomin¹^ORCID,Wang Xuesong¹^ORCID

Affiliation:

1. Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, China University of Mining and Technology, Xuzhou, China

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Key Research and Development Program of Jiangsu Province

Natural Science Foundation of Jiangsu Province

Excellent Post Doctorate Program of Jiangsu Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6046/10384483/10417796.pdf?arnumber=10417796

Reference38 articles.

1. PLTD: Patch-Based Low-Rank Tensor Decomposition for Hyperspectral Images

2. Multiscale Superpixel-Based Hyperspectral Image Classification Using Recurrent Neural Networks With Stacked Autoencoders

3. A Spectral-Spatial-Dependent Global Learning Framework for Insufficient and Imbalanced Hyperspectral Image Classification

4. Coupled adversarial learning for fusion classification of hyperspectral and LiDAR data

5. Multi-attentive hierarchical dense fusion net for fusion classification of hyperspectral and LiDAR data

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1. Statistical Texture Awareness Network for Hyperspectral Image Classification;IEEE Transactions on Geoscience and Remote Sensing;2024

2. Hyperspectral and LiDAR Classification via Frequency Domain-Based Network;IEEE Transactions on Geoscience and Remote Sensing;2024