Blaze Fire Classification – Segmentation Dataset
<p>The dataset is destined to be used for wildfire image classification and burnt area segmentation tasks for Unmanned Aerial Vehicles. It is comprised of 5,408 frames of aerial views taken from 56 videos and 2 public datasets. From the D-Fire public dataset, 829 photographs were used; and from the Burned Area UAV public dataset 34 images were used. For the classification task, there are 5 classes (‘Burnt’, ‘Half-Burnt’, ’Non-Burnt’, ‘Fire’, ‘Smoke’). As for the segmentation task, 404 segmentation masks on a subset have been created, which assign to each pixel of the image the class ‘burnt’ or the class ‘non-burnt’.</p> <p>Details on acquiring the dataset can be found <strong><a href="https://aiia.csd.auth.gr/blaze-fire-classification-segmentation-dataset/" target="_blank" rel="noopener">here</a></strong>. </p> <p> </p>
ShareScore
44/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 20
- Reuse readiness
- 8
- Engagement
- 4
Topics
ScienceDex for faculty
Your academic CV and NIH biosketch
Make your CV in your school's format and your NIH biosketch from it, then download both as Word files.