{"id":20727833,"url":"https://github.com/protyayofficial/convsfnet","last_synced_at":"2025-06-23T00:35:14.021Z","repository":{"id":249964067,"uuid":"825719153","full_name":"protyayofficial/convsfnet","owner":"protyayofficial","description":"Enhanced disaster image classification using ConvNeXt with Squeeze-and-Excitation (SE) and Feature Pyramid Network (FPN). 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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.\n\n## Directory Structure \n\n![directory_structure](directory_structure.png)\n\n## Features\n\n- **Enhanced Model Architecture**: Integration of ConvNeXt with Squeeze-and-Excitation (SE) and Feature Pyramid Network (FPN).\n- **Improved Preprocessing**: Advanced preprocessing techniques to enhance model performance.\n- **Comprehensive Evaluation**: Detailed evaluation metrics and results for various models.\n\n## Download the Dataset\n\nTo download the dataset: https://crisisnlp.qcri.org/data/medic/MEDIC.tar.gz\n\nMore details about the dataset: https://crisisnlp.qcri.org/medic/\n\nKindly give proper citation to the original authors\n\n## Acknowledgments\nWe 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.\n\n## License\n\u003cp\u003eThis project is licensed under the \u003ca href=\"LICENSE\"\u003eMIT License\u003c/a\u003e.\u003c/p\u003e\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprotyayofficial%2Fconvsfnet","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fprotyayofficial%2Fconvsfnet","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprotyayofficial%2Fconvsfnet/lists"}