Convolutional neural network for video fire and smoke detection

By Sébastien Frizzi, Rabeb Kaabi, Moez Bouchouicha, Jean-Marc Ginoux, Eric Moreau, Farhat Fnaiech. Annual Conference of the IEEE Industrial Electronics Society, 2016

326 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/a72fbe11b1b04fd85597acff816d9d596cdee026

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Panagiotis Barmpoutis
2. Asifullah Khan
3. Kosmas Dimitropoulos
4. Anabia Sohail
5. N. Grammalidis
6. Periklis Papaioannou
7. Umme Zahoora
8. Aqsa Saeed Qureshi

In Safety, Risk, Reliability and Quality

1. Panagiotis Barmpoutis
2. Kosmas Dimitropoulos
3. N. Grammalidis
4. Periklis Papaioannou

Citations in the corpus

• A survey of the recent architectures of deep convolutional neural networks (2019, background): “Many researchers have used CNN to solve various video processing-related problems (Tong et al. 2015; Frizzi et al. 2016; Shi et al. 2017; Ullah et al. 2017; Wang et al. 2017b).”
• A Review on Early Forest Fire Detection Systems Using Optical Remote Sensing (2020, background): “[54] built a simple CNN consisting of nine layers.”