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README.md

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 license: apache-2.0
+tags:
+- Hyperspectral image classification
+- Mask autoencoder
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+# HSIMAE: A Unified Masked Autoencoder with large-scale pretraining for Hyperspectral Image Classification
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65979dfeb4b5c254cb8ed20e/vyn81w5ZnXWifmbX8By6T.png)
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65979dfeb4b5c254cb8ed20e/ItHlquQYMlzo8wVMt_aVh.png)
+
+## ✨ Highlights
+### Masked HSI Modeling with Large-Scale Pretraining
+The HSIMAE was pretrained by a large-scale HSI dataset, named HyspecNet-11k, then directly finetuned on four target classification datasets.
+
+### Multi-Scale PCA for Features Extract
+To address these distributional shifts caused by the different spectral resolutions and spectral ranges between hyperspectral sensors, a MS-PCA was used to extract the multi-scale features of HSI spectra and transform the raw spectra into fixed-length features.
+
+### Dual-branch finetuning to leverage unlabeled data of target dataset
+Dual-branch finetuning framework was proposed by using an extra unlabeled branch to further adapted the model to the distributions of the target dataset and suppressed the overfitting issue.
+
+## 🧑‍💻 Contact
+
+Wang Yue   
+E-mail: ryanwy@csu.edu.cn