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:
File size: 2,472 Bytes
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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" |