[1]Huang Wenfeng,Susan Hsu,Sun Yi,et al.Fire Detection Based on Multi-resolution Convolution Neural Network in Various Scenes[J].Journal of Zhengzhou University (Engineering Science),2019,40(05):79-83.[doi:10.13705/j.issn.1671-6833.2019.05.022]
Copy
Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
40
Number of periods:
2019 05
Page number:
79-83
Column:
Public date:
2019-10-23
- Title:
-
Fire Detection Based on Multi-resolution Convolution Neural Network in Various Scenes
- Author(s):
-
Huang Wenfeng 1; Susan Hsu 2; Sun Yi 2; Zhou Bing 2
-
1. Henan Academy of Science and Technology Information; 2. School of Information Engineering, Zhengzhou University
-
- Keywords:
-
Multi-resolution convolutional neural network; flame detection; deep learning; weakly supervised localization
- CLC:
-
-
- DOI:
-
10.13705/j.issn.1671-6833.2019.05.022
- Abstract:
-
Considering the multi-scale characteristics of various scenes for the fire detection, in this paper, we propose a fire detection algorithm based on multi-resolution convolutional neural network. This algorithm leverages the BN_Inception network as the basic structure. Different coarse and fine resolution neural networks complementarily learn the multi-scale visual features of the fire in complex scenes, while paying attention to the background environment, local targets and overall layout of the scene. We also construct a fire dataset covering most of natural scenes, and test our method in this dataset. The experiment proves that the proposed method can achieve better detection results that other methods and can be effectively applied in the real world