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Detection of Fire in Video
Poledník, Tomáš ; Hradiš, Michal (referee) ; Herout, Adam (advisor)
{This thesis deals with fire detection in video by colour analysis and machine learning, specifically deep convolutional neural networks, using Caffe framework. The aim is to create a vast set of data that could be used as the base element of machine learning detection and create a detector usable in real application. For the purposes of the project a set of tools for fire sequences creation, their segmentation and automatic labeling is proposed and created together with a large test set of short sequences with artificial modelled fire.
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Fire Detection in Images and Video
Poledník, Tomáš ; Juránková, Markéta (referee) ; Přibyl, Bronislav (advisor)
This bachelor's thesis deals with fire detection in image and video. Attention is paid to the existing methods and known approaches to fire detection. Based on the analysis of the described methods, a fire detector, monitoring the attributes of its colour and motion, is designed, implemented and tested. The implemented detector achieves true positive detection rate of up to 90%.
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Support for instruction in electric fire alarm systems
Macinka, Jiří ; Jeřábek, Jan (referee) ; Burda, Karel (advisor)
The master’s thesis „Support for instruction in electric fire alarm system” describes principles and engineering solution of electric fire alarm system. It is background for activity task about EPS for students in VUT in Brno. It illustrates how to act on this task and configuration fire panel and components EPS with the support of software FSP 5000. The practice contains proposal EPS with support in fire system designer.
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Fire and smoke detection in video
Buzovský, Viktor ; Říha, Kamil (referee) ; Přinosil, Jiří (advisor)
Thesis deals with possibilities regarding detection of fire and smoke in real enviroment video. The main task is to choose suitable model, train this model, and improve detection capabilities of the model afterwards. First part of thesis is summary of theoritical knowledge needed to have understanding of discussed technical necessities. The second, practical part presents the learned model and its subsequent attempts at improvement, firstly using optical flow and then using additional classification networks. The work is concluded with a final implementation for the detector of fire and smoke, and a proposal for its potential improvement is presented. The work also includes the datasets used and created, among other things.
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Fire Detection in Video Sequences
Vampola, Radek ; Vaďura, Jiří (referee) ; Španěl, Michal (advisor)
This bachelor´s thesis deals with fire detection in video recording. The aim is to design and create a fire detector to detect incipient fire. Fire detection takes advantage of some properties of fire, which can be recorded on a camera, such as colour of fire, flickering of flames and pulsating of intensity of light emitted by fire. When fire is detected the detector highlights a fire area and a warning message is displayed in standard output.
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Fire Detection in Images and Video
Poledník, Tomáš ; Juránková, Markéta (referee) ; Přibyl, Bronislav (advisor)
This bachelor's thesis deals with fire detection in image and video. Attention is paid to the existing methods and known approaches to fire detection. Based on the analysis of the described methods, a fire detector, monitoring the attributes of its colour and motion, is designed, implemented and tested. The implemented detector achieves true positive detection rate of up to 90%.
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Smoke and Fire Detection in Video Sequences
Havelka, Robert ; Juránek, Roman (referee) ; Španěl, Michal (advisor)
This master's thesis deals with fire detection in videosequences. Attention is paid to the known characteristics of fire and basic principles of existing solutions which deal with this issue. The thesis also describes design, implementation and testing of a fire detector that is based on the recognition of suspicious areas by fire color modeling, combined with detection of motion and light intensity variations.
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Detection of Fire in Video
Poledník, Tomáš ; Hradiš, Michal (referee) ; Herout, Adam (advisor)
{This thesis deals with fire detection in video by colour analysis and machine learning, specifically deep convolutional neural networks, using Caffe framework. The aim is to create a vast set of data that could be used as the base element of machine learning detection and create a detector usable in real application. For the purposes of the project a set of tools for fire sequences creation, their segmentation and automatic labeling is proposed and created together with a large test set of short sequences with artificial modelled fire.
|
|
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Support for instruction in electric fire alarm systems
Macinka, Jiří ; Jeřábek, Jan (referee) ; Burda, Karel (advisor)
The master’s thesis „Support for instruction in electric fire alarm system” describes principles and engineering solution of electric fire alarm system. It is background for activity task about EPS for students in VUT in Brno. It illustrates how to act on this task and configuration fire panel and components EPS with the support of software FSP 5000. The practice contains proposal EPS with support in fire system designer.
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