ITER: Image-to-Pixel Representation for Weakly Supervised HSI Classification-Reference-Cited by-同舟云学术

ITER: Image-to-Pixel Representation for Weakly Supervised HSI Classification

Published:2024 Issue: Volume:33 Page:257-272
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Yang Jiaqi¹^ORCID,Du Bo²^ORCID,Wang Di³^ORCID,Zhang Liangpei¹^ORCID

Affiliation:

1. State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China

2. Hubei Key Laboratory of Multimedia and Network Communication Engineering and the National Engineering Research Center for Multimedia Software, School of Computer Science, Institute of Artificial Intelligence, Wuhan University, Wuhan, China

3. School of Computer Science, Wuhan University, Wuhan, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/10346232/10325566.pdf?arnumber=10325566

Reference65 articles.

1. Deep building footprint update network: A semi-supervised method for updating existing building footprint from bi-temporal remote sensing images

2. NSCKL: Normalized Spectral Clustering With Kernel-Based Learning for Semisupervised Hyperspectral Image Classification

3. Graph Information Aggregation Cross-Domain Few-Shot Learning for Hyperspectral Image Classification

4. Deep Network With Irregular Convolutional Kernels and Self-Expressive Property for Classification of Hyperspectral Images

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

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