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Title:Razvoj sistema za zaznavo oglasov s pomočjo strojnega učenja : magistrsko delo
Authors:ID Abraham, Leon (Author)
ID Holobar, Aleš (Mentor) More about this mentor... New window
ID Frančič, Aljaž (Comentor)
Files:.pdf MAG_Abraham_Leon_2023.pdf (3,44 MB)
MD5: C68B8D252DAD24A6EBA96803818A7801
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Magistrsko delo opisuje celotni postopek izdelovanje sistema za iskanje oglasa v toku posnetkov. Vsebuje predstavitev predobdelave oglasa ter posnetkov, iskanje slike v posnetku z lastno implementacijo ter s pomočjo storitve AWS Rekognition, uporabniški vmesnik ter predstavitev rezultatov oziroma testiranje sistema. Aplikacija deluje na podlagi iskanja dveh podobnih slik kjer v primeru podobnosti uporabnik dobi določene meta podatke (čas ujemanja, odstotek ujemanja ter ime datoteke) ter sliko, kdaj se je pojavil oglas v toku posnetkov. Sistem smo ovrednotili z mero F1, kjer smo dobili 100% uspešnost.
Keywords:strojno učenje, zaznava oglasov, AWS, FFMPEG
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[L. Abraham]
Year of publishing:2023
Number of pages:1 spletni vir (1 datoteka PDF (X, 61 f.))
PID:20.500.12556/DKUM-86546 New window
UDC:004.93:004.85(043.2)
COBISS.SI-ID:183114755 New window
Publication date in DKUM:22.12.2023
Views:844
Downloads:117
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:11.12.2023

Secondary language

Language:English
Title:Development of ad detection system with machine learning algorithms
Abstract:The master's thesis describes the entire process of creating a system for searching of advertisements in video streams. It includes the presentation of advertisement and video preprocessing, searching for an image within a video using a custom implementation and with the help of AWS Rekognition service, the user interface, and the presentation of results or system testing. The application operates based on searching for two similar images where, in the case of similarity, the user receives certain metadata (time of match in the video stream, percentage of match, and the file name) and the image of the advertisement that appeared in the video stream. The system was evaluated using the F1 measure, where it achieved a 100% success rate.
Keywords:machine learning, ad detection, AWS, FFMPEG


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