# transfer_learning_cspt

**Repository Path**: diidid/transfer_learning_cspt

## Basic Information

- **Project Name**: transfer_learning_cspt
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-02-06
- **Last Updated**: 2025-02-06

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Consecutive Pretraining: A Knowledge Transfer Learning Strategy with Unlabelled Data for Remote Sensing Domain Promotion


### This repository contains PyTorch implementation and pretrained models of CSPT. 
### Give a star! ⭐️ if this project helped you.



### Pretrained models:
The pre-trained models based on ViT-B are released in [Model Zoo](https://pan.baidu.com/s/1bhxdjjrVk0jWMs7dnXVQWQ) (code:dspt).




### Updates🌟 :
* May 7, 2022: All pretrained models of various remote sensing downstream tasks are released publicly.
* August 1, 2022: Update the code about pre-training and fine-tuning.


### Installation🚀:
Please refer to [install.md](install.md) for installation.

### Getting Started🚀: 
Please refer to [get_started.md](get_started.md) for the basic usage.

### Acknowledgement
The code is built using the [MAE](https://github.com/facebookresearch/mae), [MMdetection](https://github.com/open-mmlab/mmdetection) and [BEiT](https://github.com/microsoft/unilm/tree/master/beit) repository.

### Citation
```bash
@article{zhang2022consecutive,
  title={Consecutive pre-training: A knowledge transfer learning strategy with relevant unlabeled data for remote sensing domain},
  author={Zhang, Tong and Gao, Peng and Dong, Hao and Zhuang, Yin and Wang, Guanqun and Zhang, Wei and Chen, He},
  journal={Remote Sensing},
  volume={14},
  number={22},
  pages={5675},
  year={2022},
  publisher={MDPI}
}
```