Supervise-Assisted Self-Supervised Deep-Learning Method for Hyperspectral Image Restoration-Reference-Cited by-同舟云学术

Supervise-Assisted Self-Supervised Deep-Learning Method for Hyperspectral Image Restoration

Published:2024 Issue: Volume: Page:1-14
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Li Miaoyu¹,Fu Ying²^ORCID,Zhang Tao³^ORCID,Wen Guanghui⁴^ORCID

Affiliation:

1. School of Computer Science and Technology, Beijing Key Laboratory of Intelligent Information Technology, Beijing Institute of Technology, Beijing, China

2. the MIIT Key Laboratory of Complex-Field Intelligent Exploration, and the School of Computer Science and Technology, Beijing Key Laboratory of Intelligent Information Technology, Beijing Institute of Technology, Beijing, China

3. School of Communication Engineering, Hangzhou Dianzi University, Hangzhou, China

4. Department of Mathematics, Southeast University, Nanjing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/10526288.pdf?arnumber=10526288

Cited by 3 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. DDL: Empowering Delivery Drones With Large-Scale Urban Sensing Capability;IEEE Journal of Selected Topics in Signal Processing;2024-04

2. Siamese-DETR for Generic Multi-Object Tracking;IEEE Transactions on Image Processing;2024

3. SSUMamba: Spatial-Spectral Selective State Space Model for Hyperspectral Image Denoising;IEEE Transactions on Geoscience and Remote Sensing;2024