prikaz prve stranice dokumenta Removal of motion blur in images of human faces using deep learning
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master's thesis
Removal of motion blur in images of human faces using deep learning
2024. urn:nbn:hr:166:343609
Franov, Marcelo
University of Split
Faculty of Science
Department of Informatics

Cite this document

Franov, M. (2024). Removal of motion blur in images of human faces using deep learning (Master's thesis). Split: University of Split, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:166:343609

Franov, Marcelo. "Removal of motion blur in images of human faces using deep learning." Master's thesis, University of Split, Faculty of Science, 2024. https://urn.nsk.hr/urn:nbn:hr:166:343609

Franov, Marcelo. "Removal of motion blur in images of human faces using deep learning." Master's thesis, University of Split, Faculty of Science, 2024. https://urn.nsk.hr/urn:nbn:hr:166:343609

Franov, M. (2024). 'Removal of motion blur in images of human faces using deep learning', Master's thesis, University of Split, Faculty of Science, accessed 23 November 2024, https://urn.nsk.hr/urn:nbn:hr:166:343609

Franov M. Removal of motion blur in images of human faces using deep learning [Master's thesis]. Split: University of Split, Faculty of Science; 2024 [cited 2024 November 23] Available at: https://urn.nsk.hr/urn:nbn:hr:166:343609

M. Franov, "Removal of motion blur in images of human faces using deep learning", Master's thesis, University of Split, Faculty of Science, Split, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:166:343609

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Metadata
TitleRemoval of motion blur in images of human faces using deep learning
Title (croatian)Uklanjanje zamućenja kretanja na slikama ljudskog lica korištenjem dubokog učenja
AuthorMarcelo Franov
MentorSaša Mladenović (mentor)
Committee memberSaša Mladenović (predsjednik povjerenstva)
Committee memberGoran Zaharija (član povjerenstva)
Committee memberNika Jerković (član povjerenstva)
GranterUniversity of Split
Faculty of Science
(Department of Informatics)
Split
Defense date and country2024-09-20, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Facial image degradation by motion blur is a problem that continues to occur with the increased usage and presence of cameras in our daily lives. Whether the purpose of image capturing is personal use or further higher level computer vision tasks, they both require deblurred facial image. This thesis covers the latest literature and describes every aspect of facial deblurring problem. The importance of training dataset is tested by training different models on different facial datasets. After the trained models are tested and compared in detail the discovered conclusions were used for further development and testing of deblurring models with the emphasis on common problems and limitations.
Abstract (croatian)
Degradacija slike lica zbog zamućenja kretanja problem je koji se i dalje javlja s povećanom upotrebom i prisutnošću kamera u našem svakodnevnom životu. Bilo da je svrha snimanja slike osobna upotreba ili daljnji zadaci više razine računalnog vida, oboje zahtijevaju uklanjanje zamućenja slike lica. Ovaj rad pokriva najnoviju literaturu i opisuje svaki aspekt problema uklanjanja zamućenja lica. Važnost skupa podataka za treniranje testirana je treniranjem različitih modela na različitim skupovima podataka lica. Nakon što su uvježbani modeli testirani i detaljno uspoređeni, otkriveni zaključci korišteni su za daljnji razvoj i testiranje modela uklanjanja zamućenja s naglaskom na uobičajene probleme i ograničenja.
Keywords
Keywords (croatian)
Languageenglish
URN:NBNurn:nbn:hr:166:343609
Study programmeTitle: Data Science and Engineering
Study programme type: university
Study level: graduate
Academic / professional title: sveučilišni/a magistar/magistra podatkovne znanosti i inženjerstva (sveučilišni/a magistar/magistra podatkovne znanosti i inženjerstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2024-09-23 13:00:17