Prototypical Rebalancing Network With Semantic Alignment for Multimodal Remote Sensing Image Classification

The effective utilization of multimodal heterogeneous data can significantly improve the accuracy of remote sensing land-cover classification. However, simply introducing extra network structures for fusion causes modality imbalance, where the dominant modality interferes with the learning rate and...

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Auteurs principaux:	Lijia Dong, Jie Geng, Wen Jiang
Format:	Artigo
Langue:	Inglês
Publié:	IEEE 2025-01-01
Collection:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Sujets:	Imbalance factor modality rebalancing multimodal fusion classification semantic alignment
Accès en ligne:	https://ieeexplore.ieee.org/document/11217311/
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