Anomaly segmentation using neural networks – Bc. Václav Hloušek
Bc. Václav Hloušek
Master's thesis
Anomaly segmentation using neural networks
Anomaly segmentation using neural networks
Abstract:
Cílem práce je prozkoumat nové a úspěšné metody pro detekci anomálií které používají neuronové sítě v semi-supervised módu. Tyto metody detekují anomálie v obrazech z industriálního prostředí. Takové anomálie jsou obecně těžko detekovatelné tudíž pro dané metody je třeba aby byly přesné. Metody také lokalizují anomálie takže na jejich výstupu se nachází teplotní mapa. Poskytuji vysvětlení čtyř metod …moreAbstract:
The goal of this thesis is to examine recent successful anomaly detection methods which use neural networks in semi-supervised mode. These methods aim to detect anomalies on images from industrial setting. In this setting the anomalies are usually difficult to detect, hence the methods are required to have high accuracy. Furthermore, the methods locate the anomalies so their output is in the form of …more
Language used: English
Date on which the thesis was submitted / produced: 15. 12. 2023
Identifier:
https://is.muni.cz/th/s1f79/
Thesis defence
- Date of defence: 6. 2. 2024
- Supervisor: doc. RNDr. Pavel Matula, Ph.D.
- Reader: RNDr. Filip Lux
Full text of thesis
Contents of on-line thesis archive
Published in Theses:- světu
Other ways of accessing the text
Institution archiving the thesis and making it accessible: Masarykova univerzita, Fakulta informatikyMasaryk University
Faculty of InformaticsMaster programme / field:
Visual informatics / Image Processing and Analysis
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