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HSIMAE

Hyperspectral image classification
Mask autoencoder
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license: apache-2.0
tags:
  - Hyperspectral image classification
  - Mask autoencoder

HSIMAE: A Unified Masked Autoencoder with large-scale pretraining for Hyperspectral Image Classification

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✨ Highlights

Large-Scale and Diverse Dataset for HSI Pretraining

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.

New MAE Architecture for HSI domain

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.

Dual-branch finetuning to leverage unlabeled data of target dataset

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.

🧑‍💻 Contact

Wang Yue
E-mail: [email protected]