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

Recent years have witnessed the superiority of deep learning-based algorithms in the field of HSI classification. However, a prerequisite for the favorable performance of these methods is a large number of refined pixel-level annotations. Due to atmospheric changes, sensor differences, and complex l...

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Veröffentlicht in:	IEEE transactions on image processing Jg. 33; S. 1
Hauptverfasser:	Yang, Jiaqi, Du, Bo, Wang, Di, Zhang, Liangpei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.01.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptation models Algorithms Annotations Classification Feature extraction high frequency-aware HSI classification Hyperspectral imaging Image classification image-level annotation Labeling Labels Land cover Machine learning Pixels Representations Supervised learning Training Transformers Weakly supervised learning
ISSN:	1057-7149, 1941-0042, 1941-0042
Online-Zugang:	Volltext
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