Dual-Branch Feature Fusion Network Based Cross-Modal Enhanced CNN and Transformer for Hyperspectral and LiDAR Classification-Reference-Cited by-同舟云学术

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Dual-Branch Feature Fusion Network Based Cross-Modal Enhanced CNN and Transformer for Hyperspectral and LiDAR Classification

Published:2024 Issue: Volume:21 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Wang Wuli¹^ORCID,Li Chong¹^ORCID,Ren Peng¹^ORCID,Lu Xinchao¹,Wang Jianbu²,Ren Guangbo²,Liu Baodi³^ORCID

Affiliation:

1. College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, China

2. Laboratory of Marine Physics and Remote Sensing, First Institute of Oceanography, Ministry of Natural Resources, Qingdao, China

3. College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China

Funder

Funds of the National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Key Laboratory of Land Satellite Remote Sensing Application, Ministry of Natural Resources of the People's Republic of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/8859/10365397/10439261.pdf?arnumber=10439261

Reference17 articles.

1. Hyperspectral Image Classification—Traditional to Deep Models: A Survey for Future Prospects

2. 3-D Deep Learning Approach for Remote Sensing Image Classification

3. 3d Object Detection For Autonomous Driving Using Temporal Lidar Data

4. More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification

5. Multisource Remote Sensing Data Classification Based on Convolutional Neural Network

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