A Specialized Lightweight Fire & Smoke Detection Model for Real-Time IoT Applications
(Preprint of the research paper on this work is available at https://arxiv.org/abs/1905.11922v2. Please consider citing if you happen to use the codes or dataset.
@article{jadon2019firenet,
title={Firenet: A specialized lightweight fire \& smoke detection model for real-time iot applications},
author={Jadon, Arpit and Omama, Mohd and Varshney, Akshay and Ansari, Mohammad Samar and Sharma, Rishabh},
journal={arXiv preprint arXiv:1905.11922},
year={2019}
}
In our paper we showed results on two datasets:
- A self created diverse dataset with images randomly sampled from our self-shot fire and non-fire videos.
- Foggia's dataset (used for testing), which is available here (https://mivia.unisa.it/datasets/video-analysis-datasets/fire-detection-dataset/).
It needs to be mentioned that the data used for training is only our custom created dataset, and not Foggia's full dataset. Testing was performed on previously held-out samples from our dataset as well as on Foggia's dataset.
The following is the link to our dataset used in the FireNet paper: