Fire Detection using Deeplabv3+with Mobilenetv2

被引：2

作者：

Harkat, Houda ^{[1
,2
]}

Nascimentot, Jose M. P. ^{[3
,4
]}

Bernardinot, Alexandre ^{[5
]}

机构：

[1] Inst Super Tecn, Inst Telecomunicacoes, Ave Rovisco Pais 1, P-1049001 Lisbon, Portugal

[2] Univ Sidi Mohamed Ben Abdellah, Route Imouzzer,BP 2626, Fes 30000, Morocco

[3] IPL, Inst Telecomunicacoes, Lisbon, Portugal

[4] IPL, Inst Super Engn Lisboa, Lisbon, Portugal

[5] ISR Inst Sistemas & RobOt, Ave Rovisco Pais 1, P-1049001 Lisbon, Portugal

来源：

2021 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM IGARSS | 2021年

关键词：

Fire; detection system; Deeplabv3+; Mobilinetv2; Corsican french dataset;

D O I：

10.1109/IGARSS47720.2021.9553141

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

Fire detection is high priority task in the current decade, due to the high occurrences of fire in urban and forest area. Every year, millions of hectares of forests are burned and destroyed. The cost of dislocation could be optimized by implementing an accurate detection system. In this paper a Deeplabv3+ model with a Mobilenetv2 backbone is implemented and tested over R GB and Infrared pictures of the Corsican french dataset. Three different types of loss function were used to overcome the problem of unbalanced dataset. The results obtained with the model herein presented are very encouraging.

引用

页码：4095 / 4098

页数：4

共 13 条

[1] CaMap: Camera-based Map Manipulation on Mobile Devices [J].

Chen, Liang ;

Chen, Dongyi .

PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND APPLICATION ENGINEERING (CSAE2018), 2018,

[2] DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs [J].

Chen, Liang-Chieh ;

Papandreou, George ;

Kokkinos, Iasonas ;

Murphy, Kevin ;

Yuille, Alan L. .

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2018, 40 (04) :834-848

[3]

Chen LB, 2017, IEEE INT SYMP NANO, P1, DOI 10.1109/NANOARCH.2017.8053709

[4] Generalized overlap measures for evaluation and validation in medical image analysis [J].

Crum, William R. ;

Camara, Oscar ;

Hill, Derek L. G. .

IEEE TRANSACTIONS ON MEDICAL IMAGING, 2006, 25 (11) :1451-1461

[5] Automatic Early Smoke Segmentation based on Conditional Generative Adversarial Networks [J].

Jia, Yang ;

Du, Hanrong ;

Wang, Haijuan ;

Yu, Runyang ;

Fan, Lianghui ;

Xu, Gao ;

Zhang, Qixing .

OPTIK, 2019, 193

[6] Smoke Detection on Video Sequences Using 3D Convolutional Neural Networks [J].

Lin, Gaohua ;

Zhang, Yongming ;

Xu, Gao ;

Zhang, Qixing .

FIRE TECHNOLOGY, 2019, 55 (05) :1827-1847

[7]

Mlich Jozef, 2020, Advanced Concepts for Intelligent Vision Systems. 20th International Conference, ACIVS 2020. Proceedings. Lecture Notes in Computer Science (LNCS 12002), P27, DOI 10.1007/978-3-030-40605-9_3

[8] Two-Step Real-Time Night-Time Fire Detection in an Urban Environment Using Static ELASTIC-YOLOv3 and Temporal Fire-Tube [J].