diplomsko delo
Anej Umek (Author), Danijel Skočaj (Mentor)

Abstract

Kasete VHS so bile več kot dvajset let glavni pomnilni medij za hranjenje posnetkov. Magnetni trak, na katerem je posnetek shranjen, je precej nezanesljiv in zato tarča raznim degradacijam, ki lahko pokvarijo izkušnjo gledanja posnetka. Z namenom odstranitve teh degradacij smo nadgradili metodo globokega učenja TAPE, ki sloni na transformerski arhitekturi. Model smo naučili na avtentičnih posnetkih VHS, ki smo jih pridobili z nalaganjem posnetkov na kaseto VHS in digitaliziranjem z nje. Naučili smo splošen model in tri specializirane modele, ki smo jih ovrednotili in primerjali. Najboljše rezultate je dosegel splošen model, ki je mere uspešnosti izboljšal za 20 do 30 %.

Keywords

transformer;restavracija;posnetki VHS;restavracija posnetkov;univerzitetni študij;diplomske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UL FRI - Faculty of Computer and Information Science
Publisher: [A. Umek]
UDC: 004.85:621.397(043.2)
COBISS: 211585539 Link will open in a new window
Views: 131
Downloads: 47
Average score: 0 (0 votes)
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Other data

Secondary language: English
Secondary title: Restoration of digitized VHS tapes
Secondary abstract: For more than twenty years, VHS tapes were the main storage medium for storing recordings. The magnetic tape on which the recording is stored is quite unreliable and therefore a target for various degradations that can ruin the experience of watching the recording. To remove these degradations, we enhanced the deep learning method TAPE, which is based on a transformer architecture. We trained the model on authentic VHS recordings obtained by loading the recordings onto VHS tape and digitizing them from it. We learned the general model and three specialized models, which we evaluated and compared. The best results were achieved by the general model which improved evaluation metrics by 20 to 30 %.
Secondary keywords: transformer;restoration;VHS recordings;computer and information science;diploma;Videoposnetki;Globoko učenje (strojno učenje);Računalništvo;Univerzitetna in visokošolska dela;
Type (COBISS): Bachelor thesis/paper
Study programme: 1000468
Embargo end date (OpenAIRE): 1970-01-01
Thesis comment: Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages: 1 spletni vir (1 datoteka PDF (58 str.))
ID: 24985113
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