--- license: cc-by-4.0 task_categories: - image-segmentation tags: - methane-detection - thermal-infrared - agriculture - semantic-segmentation - optical-gas-imaging - environmental-monitoring - FLIR-GF77 - enteric-methane - rumen-fermentation size_categories: - 1K ⚠️ **Important**: There is a discrepancy between pixel values and class IDs in the mask files: - Pixel value 0: Background (Class 0) - Pixel value 1: Control diet (Class 1) - Pixel value 2: **High forage diet (Class 3)** ⚠️ - Pixel value 3: **Low forage diet (Class 2)** ⚠️ ## 📋 License This dataset is released under the [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/) license. ## 📚 Additional Resources For preprocessing methods and code examples, please refer to the [GitHub repository](https://github.com/toqitahamid/controlled-diet-methane-dataset-tools). ## 🙏 Acknowledgments This work was supported by the USDA National Institute of Food and Agriculture (NIFA) under Grant No. 2022-70001-37404. ## 📜 Citation This work is published in IET Image Processing (2025, DOI: 10.1049/ipr2.13327). ```bibtex @article{embaby2025optical, title={Optical gas imaging and deep learning for quantifying enteric methane emissions from rumen fermentation in vitro}, author={Embaby, Mohamed G and Sarker, Toqi Tahamid and AbuGhazaleh, Amer and Ahmed, Khaled R}, journal={IET Image Processing}, year={2025}, doi={10.1049/ipr2.13327} } ```