@inproceedings{346664681a5a435b9b308a3b250314a2,
title = "Videoda gece yangini tespiti",
abstract = "There has been increasing interest in the study of video based fire detection as video based surveillance systems become widely available for indoor and outdoor monitoring applications. Video based fire detection methods in computer vision literature do not take into account whether the fire takes place in the day time or at night. A novel method explicitly developed for video based detection of fire at night (in the dark) is presented in this paper. The method comprises three sub-algorithms each of which characterizes certain part of fire at night. Individual decisions of the sub-algorithms are combined together using a least-mean-square based decision fusion approach.",
author = "Kasim Ta{\c s}demir and Osman G{\"u}nay and T{\"o}reyin, \{B. Uǧur\} and {\c C}etin, \{A. Enis\}",
year = "2009",
doi = "10.1109/SIU.2009.5136497",
language = "T{\"u}rk{\c c}e",
isbn = "9781424444366",
series = "2009 IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009",
pages = "720--723",
booktitle = "2009 IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009",
note = "2009 IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009 ; Conference date: 09-04-2009 Through 11-04-2009",
}