Analysis and Design of a Yolo like DNN for Smoke/Fire Detection for Low-cost Embedded Systems

Author:

Gagliardi Alessio,Villella Marco,Picciolini Luca,Saponara Sergio

Publisher

Springer International Publishing

Reference18 articles.

1. Vijayalakshmi, S.R., Muruganand, S.: Smoke detection in video images using background subtraction method for early fire alarm system. In: 2017 2nd International Conference on Communication and Electronics Systems (ICCES), pp. 167–171 (2017)

2. Çelik, T., Özkaramanlı, H., Demirel, H.: Fire and smoke detection without sensors: image processing-based approach. In: IEEE 15th European Signal Processing Conference, pp. 1794–1798 (2007)

3. Zhang, Q., et al.: Dissipation function and ViBe based smoke detection in video. In: 2017 2nd International Conference on Multimedia and Image Processing (ICMIP). IEEE, pp. 325–329 (2017)

4. Gagliardi, A., Saponara, S.: AdViSED: advanced video smoke detection for real-time measurements in antifire indoor and outdoor systems. Energies, 13(8), 2020

5. Ehlnashi, A., Gagliardi, A., Saponara, S.: Exploiting R-CNN for video smoke/fire sensing in antifire surveillance indoor and outdoor systems for smart cities. In: IEEE 6th International Conference on Smart Computing (SSC), Bologna, Italy, September 2020

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