prikaz prve stranice dokumenta Detekcija biciklista u video snimci dubokim neuronskim mrežama
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master's thesis
Detekcija biciklista u video snimci dubokim neuronskim mrežama
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. urn:nbn:hr:168:045241
Radić, Iva
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Radić, I. (2017). Detekcija biciklista u video snimci dubokim neuronskim mrežama (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:045241

Radić, Iva. "Detekcija biciklista u video snimci dubokim neuronskim mrežama." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. https://urn.nsk.hr/urn:nbn:hr:168:045241

Radić, Iva. "Detekcija biciklista u video snimci dubokim neuronskim mrežama." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. https://urn.nsk.hr/urn:nbn:hr:168:045241

Radić, I. (2017). 'Detekcija biciklista u video snimci dubokim neuronskim mrežama', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 29 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:045241

Radić I. Detekcija biciklista u video snimci dubokim neuronskim mrežama [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2017 [cited 2024 November 29] Available at: https://urn.nsk.hr/urn:nbn:hr:168:045241

I. Radić, "Detekcija biciklista u video snimci dubokim neuronskim mrežama", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:168:045241

Metadata
TitleDetekcija biciklista u video snimci dubokim neuronskim mrežama
Title (english)Cyclist Detection from Video Using Deep Neural Networks
AuthorIva Radić
MentorSven Lončarić (mentor)
Committee memberSven Lončarić (predsjednik povjerenstva)
Committee memberMarko Subašić (član povjerenstva)
Committee memberTomislav Petković (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2017-07-14, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U radu je predstavljen problem detekcije objekata u slici, te problem detekcije i praćenja objekata kroz slijedne slike u videosnimci. Uz povjesni pregled, predstavljena su i dosadašnja dostignuća u brzoj i točnoj detekciji objekata. Model korišten u implementaciji sustava za detekciju je potpuno konvolucijski SqueezeDet model. Za korištenje temporalne informacije kao pomoć detekciji objekata u videu razmotrena su dva algoritma, MedianFlow i MIL praćenje. Sustav provodi detekciju s preciznošću od 62.3%
Abstract (english)
This paper presents the problem of object detection in image, and the problem of detecting and tracking objects through sequential images in video clips. Along with the historic review, the paper presents recent achievements in fast and accurate object detection. The model used in the detection system implementation is the fully convolutional SqueezeDet model. Two tracking algorithms, MedianFlow and MIL tracking were considered. Tracking is used to improve accuracy of detection in video. The system performs detection with accuracy of 62.3%
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:045241
Study programmeTitle: Information and Communication Technology
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka informacijske i komunikacijske tehnologije (magistar/magistra inženjer/inženjerka informacijske i komunikacijske tehnologije)
Type of resourceText
File originBorn digital
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Created on2019-03-14 00:17:43