Fire Segmentation in Still Images

Author:

Mlích JozefORCID,Koplík KarelORCID,Hradiš MichalORCID,Zemčík PavelORCID

Publisher

Springer International Publishing

Reference16 articles.

1. Bedo, M.V.N., et al.: Techniques for effective and efficient fire detection from social media images. CoRR abs/1506.03844 (2015). http://arxiv.org/abs/1506.03844

2. Cazzolato, M.T., et al.: Fismo: a compilation of datasets from emergency situations for fire and smoke analysis. In: Proceedings of the Satellite Events (2017)

3. Çetin, A.E., et al.: Video fire detection – review. Digital Sig. Process. 23(6), 1827 – 1843 (2013). https://doi.org/10.1016/j.dsp.2013.07.003 , http://www.sciencedirect.com/science/article/pii/S1051200413001462

4. Chen, L., Papandreou, G., Schroff, F., Adam, H.: Rethinking atrous convolution for semantic image segmentation. CoRR abs/1706.05587 (2017). http://arxiv.org/abs/1706.05587

5. Chino, D.Y.T., Avalhais, L.P.S., Rodrigues, J.F., Traina, A.J.M.: Bowfire: detection of fire in still images by integrating pixel color and texture analysis. In: 2015 28th SIBGRAPI Conference on Graphics, Patterns and Images, pp. 95–102, August 2015. https://doi.org/10.1109/SIBGRAPI.2015.19

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