Приказ основних података о дисертацији

dc.contributor.advisorNikolić, Vlastimir
dc.contributor.otherĆirić, Ivan
dc.contributor.otherAntić, Dragan
dc.contributor.otherStamenković, Dušan
dc.contributor.otherSimonović, Miloš
dc.creatorPavlović, Milan G.
dc.date.accessioned2021-03-23T10:02:24Z
dc.date.available2021-03-23T10:02:24Z
dc.date.issued2020-09-28
dc.identifier.urihttp://eteze.ni.ac.rs/application/showtheses?thesesId=7963
dc.identifier.urihttps://fedorani.ni.ac.rs/fedora/get/o:1681/bdef:Content/download
dc.identifier.urihttp://vbs.rs/scripts/cobiss?command=DISPLAY&base=70052&RID=25074185
dc.identifier.urihttps://nardus.mpn.gov.rs/handle/123456789/18143
dc.descriptionThe railway is an important type of transport and has a significant economic impact on the industry and people's everyday life. Due to its capacities and complex infrastructure, it is necessary to work on its constant development and improvement. Railway automation requires the use of intelligent systems as a necessary part of an autonomous railway vehicle. As from the point of view of safe traffic, the existence of the object on the rail track and / or in its vicinity represents a potential obstacle to the railway traffic, and visibility has a very important role in correct and timely detection of the object on the railway infrastructure, a key element of autonomous railway vehicle is an obstacle detection system on the part of the railway infrastructure, in conditions of reduced visibility. The subject of scientific research of this doctoral dissertation is the application of intelligent machine vision systems in autonomous train operation. For the purpose of detecting obstacles on the part of the railway infrastructure in conditions of reduced visibility, a thermal imaging camera and a night vision system are integrated into the system, coupled with a developed advanced algorithm for image processing with artificial intelligence tools. In addition, the distance from the machine vision system to the detected object was estimated. The operation of the system was tested in a series of field experiments, at different locations, in different visibility conditions and weather conditions, through realistic scenarios.en
dc.formatapplication/pdf
dc.languagesr
dc.publisherУниверзитет у Нишу, Машински факултетsr
dc.relationinfo:eu-repo/grantAgreement/MESTD/Technological Development (TD or TR)/35005/RS//
dc.rightsopenAccessen
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceУниверзитет у Нишуsr
dc.subjectMašinska vizijasr
dc.subjectMachine visionen
dc.subjectreduced visibility conditionsen
dc.subjectdetectionen
dc.subjectdistance estimationen
dc.subjectautonomous train operationen
dc.subjectuslovi smanjene vidljivostisr
dc.subjectdetekcijasr
dc.subjectocena rastojanjasr
dc.subjectautonomno upravljanje železničkim vozilomsr
dc.titlePrimena inteligentnih sistema mašinske vizije autonomnog upravljanja železničkim vozilimasr
dc.typePhD thesis
dc.rights.licenseBY-NC-ND
dcterms.abstractНиколић, Властимир; Стаменковић, Душан; Симоновић, Милош; Aнтић, Драган; Ћирић, Иван; Павловић, Милан Г.; Примена интелигентних система машинске визије аутономног управљања железничким возилима; Примена интелигентних система машинске визије аутономног управљања железничким возилима;
dc.identifier.fulltexthttps://nardus.mpn.gov.rs/bitstream/id/70347/Pavlovic_Milan_G.pdf
dc.identifier.fulltexthttps://nardus.mpn.gov.rs/bitstream/id/70346/Disertacija.pdf
dc.identifier.rcubhttps://hdl.handle.net/21.15107/rcub_nardus_18143


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Приказ основних података о дисертацији