Deep Convolutional Generative Adversarial Network and Convolutional Neural Network for Smoke Detection
Joint Authors
Yin, Hang
Wei, Yurong
Liu, Hedan
Liu, Shuangyin
Liu, Chuanyun
Gao, Yacui
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-16
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Real-time smoke detection is of great significance for early warning of fire, which can avoid the serious loss caused by fire.
Detecting smoke in actual scenes is still a challenging task due to large variance of smoke color, texture, and shapes.
Moreover, the smoke detection in the actual scene is faced with the difficulties in data collection and insufficient smoke datasets, and the smoke morphology is susceptible to environmental influences.
To improve the performance of smoke detection and solve the problem of too few datasets in real scenes, this paper proposes a model that combines a deep convolutional generative adversarial network and a convolutional neural network (DCG-CNN) to extract smoke features and detection.
The vibe algorithm was used to collect smoke and nonsmoke images in the dynamic scene and deep convolutional generative adversarial network (DCGAN) used these images to generate images that are as realistic as possible.
Besides, we designed an improved convolutional neural network (CNN) model for extracting smoke features and smoke detection.
The experimental results show that the method has a good detection performance on the smoke generated in the actual scenes and effectively reduces the false alarm rate.
American Psychological Association (APA)
Yin, Hang& Wei, Yurong& Liu, Hedan& Liu, Shuangyin& Liu, Chuanyun& Gao, Yacui. 2020. Deep Convolutional Generative Adversarial Network and Convolutional Neural Network for Smoke Detection. Complexity،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1143408
Modern Language Association (MLA)
Yin, Hang…[et al.]. Deep Convolutional Generative Adversarial Network and Convolutional Neural Network for Smoke Detection. Complexity No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1143408
American Medical Association (AMA)
Yin, Hang& Wei, Yurong& Liu, Hedan& Liu, Shuangyin& Liu, Chuanyun& Gao, Yacui. Deep Convolutional Generative Adversarial Network and Convolutional Neural Network for Smoke Detection. Complexity. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1143408
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143408