MFINet: A Novel Zero-Shot Remote Sensing Scene Classification Network Based on Multimodal Feature Interaction

Zero-shot classification models aim to recognize image categories that are not included in the training phase by learning seen scenes with semantic information. This approach is particularly useful in remote sensing (RS) since it can identify previously unseen classes. However, most zero-shot RS sce...

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Autori principali:	Xiaomeng Tan, Bobo Xi, Haitao Xu, Yunsong Li, Changbin Xue, Jocelyn Chanussot
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	IEEE 2024-01-01
Serie:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Soggetti:	Cross-modal feature fusion (CMFF) improved Transformer remote sensing (RS) scene classification zero-shot learning (ZSL)
Accesso online:	https://ieeexplore.ieee.org/document/10557622/
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