Generiranje ultrazvučnih slika dubokim generativnim mrežama

undergraduate thesis

• Title (english): Ultrasound Image Generation Using Deep Generative Networks
• Author: Gordan Praštalo
• Mentor: Sven Lončarić (mentor)
• Committee member: Sven Lončarić (predsjednik povjerenstva)
• Committee member: Luka Posilović (član povjerenstva)
• Committee member: Duje Medak (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2021-07-15, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Nedostatak slika s defektima kod ispitivanja materijala bez razaranja predstavlja problem za automatizaciju detekcije defekata. Rad proučava uporabu dubokih generativnih mreža kao rješenje ovog problema. Cilj je ostvariti jeftiniji i pouzdaniji proces generiranja slika s defektima.

Abstract (english)

The low amount of images with defects with non-destructive testing makes automating defect detection hard. This thesis studies the use of generative networks as a solution of this problem with the goal of developing cheaper and more reliable method of generating images with defect.

• Keywords: DCGAN; D2GAN; GAN; NDT; duboko učenje; računalni vid
• Keywords (english): DCGAN; D2GAN; GAN; NDT; deep learning; computer vision
• Language: croatian
• URN:NBN: urn:nbn:hr:168:736205
• Study programme: Title: Computing; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-14 21:28:28