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pro vyhledávání: '"Karani Kardas"'
Autor:
Karani Kardas
Publikováno v:
2020 28th Signal Processing and Communications Applications Conference (SIU).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::952dd12d92f32bd9ceb392dbb35cf97d
https://doi.org/10.1109/siu49456.2020.9302439
https://doi.org/10.1109/siu49456.2020.9302439
Autor:
Nihan Kesim Cicekli, Karani Kardas
Publikováno v:
Expert Systems with Applications. 89:343-361
This paper introduces a Surveillance Video Analysis System, called SVAS, for surveillance domain, in which the semantic rules and the definition of event models can be learned or defined by the user for automatic detection and inference of complex vi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8edf720d968a32fa03c2e0b61ab426c4
https://doi.org/10.1016/j.eswa.2017.07.051
https://doi.org/10.1016/j.eswa.2017.07.051
Autor:
Karani Kardas
Publikováno v:
SIU
This study presents the use and the importance of semantic machine learning method in video event recognition. In this respect, Semantic Event Recognition System is introduced in which semantic rules and event models can be defined by the user for co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::647c2bc322cb4896e1be1c977a2955fd
https://doi.org/10.1109/siu.2018.8404849
https://doi.org/10.1109/siu.2018.8404849
Autor:
Karani Kardas, Ulya Bayram, Itir Onal, Nihan Kesim Cicekli, Ilkay Ulusoy, Murat Bal, Yousef Rezaeitabar
Publikováno v:
ICME Workshops
This paper presents a framework for detecting complex events in surveillance videos. Moving objects in the foreground are detected in the object detection component of the system. Whether these foregrounds are human or not is decided in the object re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7b23a5698e02e8fa4532ccff6d089230
https://doi.org/10.1109/icmew.2013.6618411
https://doi.org/10.1109/icmew.2013.6618411
Publikováno v:
ICME Workshops
An event model learning framework is proposed for indoor and outdoor surveillance applications in order to decrease human intervention in the modeling process. The resulting framework makes event detection and recognition flexible, domain and scene i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::daf346313ab4bd26630d68e14789c3e3
https://doi.org/10.1109/icmew.2013.6618413
https://doi.org/10.1109/icmew.2013.6618413