Multi Feature Analysis of Smoke in YUV Color Space for Early Forest Fire Detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Safety, Risk, Reliability and Quality,General Materials Science
Link
http://link.springer.com/content/pdf/10.1007/s10694-016-0580-8.pdf
Reference28 articles.
1. Enis CA, Dimitropoulos K, Gouverneur B, Grammalidis N, Gunay O, Habiboglu YH, Toreyin BU, Verstockt S (2013) Video fire detection—review. Digit Signal Proc 23: 1827–1843.
2. Qureshi WS, Ekpanyapong M, Dailey MN, Rinsurongkawong S, Malenichev A, Krasotkina O (2015) QuickBlaze: early fire detection using a combined video processing approach. Fire Technol. doi: 10.1007/s10694-015-0489-7 .
3. Ye W, Zhao J, Wang S, Wang Y, Zhang D, Yuan Z (2015) Dynamic texture based smoke detection using surfacelet wavelet transform and HMT model. Fire Saf J 73: 91–101. doi: 10.1016/j.firesaf.2015.03.001 .
4. Pagar PB, Shaikh AN (2013) Real time based fire and smoke detection without sensor by image processing. Int J Adv Electr Electron Eng 2: 25–34.
5. Maruta H, Nakamura A, Kurokawa F (2010) A new approach for smoke detection with texture analysis and support vector machine. In: IEEE International symposium on industrial electronics ISIE, 4–7 July 2010. Bari: IEEE, p. 1550–1555. doi: 10.1109/ISIE.2010.5636301 .
Cited by 59 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Review of Modern Forest Fire Detection Techniques: Innovations in Image Processing and Deep Learning;Information;2024-09-03
2. YOLO-ULNet: Ultralightweight Network for Real-Time Detection of Forest Fire on Embedded Sensing Devices;IEEE Sensors Journal;2024-08-01
3. An efficient deep learning architecture for effective fire detection in smart surveillance;Image and Vision Computing;2024-05
4. Forest Fire Smoke Detection Based on Multiple Color Spaces Deep Feature Fusion;Forests;2024-04-11
5. Improving Computer Vision-Based Wildfire Smoke Detection by Combining SE-ResNet with SVM;Processes;2024-04-07
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3