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An aggregate of works in computer vision for fire detection

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An aggregate of works in computer vision for fire detection.

Methods

Author Paper Method Own Dataset Link
Dunnings et al. Yes Deep CNN classification (InceptionV3) + superpix. loc. Yes https://github.com/tobybreckon/fire-detection-cnn
hojak99 No background substraction + red channel rule No https://github.com/hojak99/fire-detection
Yes https://github.com/cair/Fire-Detection-Image-Dataset
Steffens et al. Yes Deep CNN classification (InceptionV3) Yes https://github.com/steffensbola/furg-fire-dataset
Deep CNN classification (custom arch) + Raspberry Pi Yes https://github.com/arpit-jadon
Foggia et al. Color + Shape + Motion Features https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7014233
Zhang et al. Deep CNN detection (R-CNN) Synthetic https://www.sciencedirect.com/science/article/pii/S1877705817362574

https://github.com/ckyrkou/AIDER https://github.com/ckyrkou/EmergencyNet

Datasets

Dataset Samples Annotations Link
Foggia et al. Per-video https://mivia.unisa.it/datasets/video-analysis-datasets/fire-detection-dataset/
Aligarh Muslim University https://drive.google.com/drive/folders/1HznoBFEd6yjaLFlSmkUGARwCUzzG4whq
Dunnings, Breckon https://collections.durham.ac.uk/downloads/r2d217qp536
VisiFire http://signal.ee.bilkent.edu.tr/VisiFire/

Applications

Application Platform Code
AR Drone Fire Detection AR Drone https://github.com/Sanderi44/AR-Drone-Fire-Detection.git

Research Projects

Community-Empowered Air Quality Monitoring System, CMU RI, https://arxiv.org/pdf/1804.03293.pdf

Project RISE, CMU RI, https://smoke.createlab.org/faq.html

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