ConvSFNet: Enhanced Disaster Image Classification

This project enhances disaster image classification by building upon the Medic repository. We introduce a novel architecture combining ConvNeXt with Squeeze-and-Excitation (SE) and Feature Pyramid Network (FPN) to improve classification accuracy and address overfitting issues.

Directory Structure

Features

• Enhanced Model Architecture: Integration of ConvNeXt with Squeeze-and-Excitation (SE) and Feature Pyramid Network (FPN).
• Improved Preprocessing: Advanced preprocessing techniques to enhance model performance.
• Comprehensive Evaluation: Detailed evaluation metrics and results for various models.

Download the Dataset

To download the dataset: https://crisisnlp.qcri.org/data/medic/MEDIC.tar.gz

More details about the dataset: https://crisisnlp.qcri.org/medic/

Kindly give proper citation to the original authors

Acknowledgments

We would like to thank the authors of the Medic repository for providing a solid foundation for our work. Their initial framework was essential in developing our enhanced model.

License

This project is licensed under the MIT License.