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license: apache-2.0 |
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tags: |
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- Hyperspectral image classification |
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- Mask autoencoder |
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--- |
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# HSIMAE: A Unified Masked Autoencoder with large-scale pretraining for Hyperspectral Image Classification |
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## ✨ Highlights |
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### Large-Scale and Diverse Dataset for HSI Pretraining |
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A large and diverse HSI dataset named HSIHybrid was curated for large-scale HSI pre-training. It consisted of 15 HSI datasets from different hyperspectral sensors. After splitting into image patches, a total of **4 million** HSI patches with a spatial size of 9×9 were obtained. |
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### New MAE Architecture for HSI domain |
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A modified MAE named HSIMAE that utilized separate spatial-spectral encoders followed by fusion blocks to learn spatial correlation and spectral correlation of HSI data was proposed. |
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### Dual-branch finetuning to leverage unlabeled data of target dataset |
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A dual-branch fine-tuning framework was introduced to leverage the unlabeled data of the downstream HSI dataset and suppressed overfitting on small training samples. |
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## 🧑💻 Contact |
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Wang Yue |
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E-mail: ryanwy@csu.edu.cn |
