Joint negative–positive-learning based sample reweighting for hyperspectral image classification with label noise-Reference-Cited by-同舟云学术

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Joint negative–positive-learning based sample reweighting for hyperspectral image classification with label noise

Published:2024-07 Issue: Volume:183 Page:98-103
ISSN:0167-8655
Container-title:Pattern Recognition Letters
language:en
Short-container-title:Pattern Recognition Letters

Author:

Liao Qiming,Zhao Lin^ORCID,Luo Wenqiang,Li Xinping^ORCID,Zhang Guoyun

Publisher

Elsevier BV

Reference25 articles.

1. Hyperspectral image classification with contrastive self-supervised learning under limited labeled samples;Zhao;IEEE Geosci. Remote Sens. Lett.,2022

2. Mutual attention inception network for remote sensing visual question answering;Zheng;IEEE Trans. Geosci. Remote Sens.,2021

3. Compact band weighting module based on attention-driven for hyperspectral image classification;Zhao;IEEE Trans. Geosci. Remote Sens.,2021

4. Rotation-invariant attention network for hyperspectral image classification;Zheng;IEEE Trans. Image Process.,2022

5. Adaptive hybrid attention network for hyperspectral image classification;Pande;Pattern Recognit. Lett.,2021

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