Automatic framework for semi-supervised hyperspectral image classification using self-training with data editing-Reference-Cited by-同舟云学术

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Automatic framework for semi-supervised hyperspectral image classification using self-training with data editing

Published:2015-06 Issue: Volume: Page:
ISSN:
Container-title:2015 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)
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Author:

Wang Junshu,Jiang Nan,Zhang Guoming,Hu Bin,Li Yang

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8053871/8075362/08075485.pdf?arnumber=8075485

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. Detection Is Better Than Cure: A Cloud Incidents Perspective;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30

2. Spectral-Spatial Classification Of Hyperspectral Images With Multi-Level Cnn;2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS);2022-09-13

3. Applying Efficient Selection Techniques of Unlabeled Instances for Wrapper-Based Semi-Supervised Methods;IEEE Access;2022

4. Small sample classification of hyperspectral image using model-agnostic meta-learning algorithm and convolutional neural network;International Journal of Remote Sensing;2021-01-20

5. Hyperspectral image super-resolution combining with deep learning and spectral unmixing;Signal Processing: Image Communication;2020-05

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