Datasets:
Tasks:
Image Segmentation
Modalities:
Image
Languages:
English
Size:
1K<n<10K
Tags:
methane-detection
thermal-infrared
agriculture
semantic-segmentation
optical-gas-imaging
environmental-monitoring
License:
| cff-version: 1.2.0 | |
| title: "Controlled Diet (CD) Dataset for Methane Plume Detection" | |
| message: "If you use this dataset, please cite both the dataset and the accompanying research paper." | |
| type: dataset | |
| authors: | |
| - family-names: "Embaby" | |
| given-names: "Mohamed G." | |
| orcid: "https://orcid.org/0000-0002-9695-3433" | |
| - family-names: "Sarker" | |
| given-names: "Toqi Tahamid" | |
| orcid: "https://orcid.org/0000-0003-2482-8059" | |
| - family-names: "AbuGhazaleh" | |
| given-names: "Amer" | |
| orcid: "https://orcid.org/0000-0003-1589-2358" | |
| - family-names: "Ahmed" | |
| given-names: "Khaled R." | |
| orcid: "https://orcid.org/0000-0002-3707-4316" | |
| repository-code: "https://github.com/toqitahamid/controlled-diet-methane-dataset" | |
| url: "https://huggingface.co/datasets/toqi/controlled-diet-methane" | |
| abstract: >- | |
| The Controlled Diet (CD) dataset is a large-scale collection of 4,885 methane (CH₄) | |
| plume images captured using optical gas imaging (OGI) technology for semantic | |
| segmentation tasks. This dataset was developed to investigate the detection and | |
| quantification of enteric methane emissions from ruminants under different dietary | |
| conditions using computer vision and deep learning techniques. The dataset contains | |
| methane plumes categorized into three classes based on Gas Chromatography (GC) | |
| measured concentration ranges corresponding to different dietary treatments: | |
| Control (166-171 ppm), Low Forage (300-334 ppm), and High Forage (457-510 ppm). | |
| keywords: | |
| - "optical gas imaging" | |
| - "methane detection" | |
| - "semantic segmentation" | |
| - "livestock emissions" | |
| - "computer vision" | |
| - "deep learning" | |
| - "agriculture" | |
| - "climate change" | |
| - "FLIR GF77" | |
| license: "CC-BY-4.0" | |
| version: "1.0.0" | |
| date-released: "2025-01-19" | |
| identifiers: | |
| - type: "doi" | |
| value: "10.1049/ipr2.13327" | |
| description: "Accompanying research paper DOI" | |
| preferred-citation: | |
| type: article | |
| title: "Optical gas imaging and deep learning for quantifying enteric methane emissions from rumen fermentation in vitro" | |
| authors: | |
| - family-names: "Embaby" | |
| given-names: "Mohamed G." | |
| - family-names: "Sarker" | |
| given-names: "Toqi Tahamid" | |
| - family-names: "AbuGhazaleh" | |
| given-names: "Amer" | |
| - family-names: "Ahmed" | |
| given-names: "Khaled R." | |
| journal: "IET Image Processing" | |
| year: 2025 | |
| publisher: | |
| name: "Institution of Engineering and Technology" | |
| doi: "10.1049/ipr2.13327" | |
| url: "https://doi.org/10.1049/ipr2.13327" |