Full description
This dataset contains 11027 labeled images for the detection of fire and smoke instances in diverse real-world scenarios. The annotations are provided in YOLO format with bounding boxes and class labels for two classes: fire and smoke. The dataset is divided into an 80% training set with 10,090 fire instances and 9724 smoke instances, a 10% Validation set with 1,255 fire and 1,241 smoke instances, and a 10% Test set with 1,255 fire and 1,241 smoke instances. This dataset is suitable for training and evaluating fire and smoke detection models, such as YOLOv8, YOLOv9, and similar deep learning-based frameworks in the context of emergency response, wildfire monitoring, and smart surveillance.Issued: 2025-04-14
Created: 2025-04-14
Subjects
Deep learning |
Fire detection |
Planning and decision making |
Semi- and unsupervised learning |
UAV fire monitoring |
YOLO |
YOLO annotations |
smoke detection |
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Identifiers
- DOI : 10.25946/28747046.V1