Tool for data pre-processing and iterative learning of neural networks – Bc. Kristián Malák
Bc. Kristián Malák
Bachelor's thesis
Tool for data pre-processing and iterative learning of neural networks
Tool for data pre-processing and iterative learning of neural networks
Abstract:
Táto Bakalárska práca popisuje tvorbu aplikačného rozhrania pre súkromnú spoločnosť. Dané aplikačné rozhranie bude použité ako súčasť nástroja na tréning neurónových sietí, ktoré budú používané na detekciu povrchových chýb, vo výrobe. Spomínaný nástroj natrénuje neurónovú sieť pomocou techniky zvanej iteratívne učenie. Z technického hľadiska, aplikačné rozhranie (API), sprostedkuje službu iteratívneho …moreAbstract:
This Bachelor thesis describes building of an application interface for a private company. This application interface is to be used as a part of a tool designed for training neural networks, which will be used for detecting surface defects, in manufacturing. Said tool will train a neural network by employing a technique called iterative learning. Technically, the application interface (API), provides …more
Language used: English
Date on which the thesis was submitted / produced: 16. 12. 2021
Identifier:
https://is.muni.cz/th/wh6n6/
Thesis defence
- Date of defence: 11. 2. 2022
- Supervisor: doc. RNDr. Pavel Matula, Ph.D.
- Reader: RNDr. Filip Lux
Citation record
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 InformaticsBachelor programme / field:
Informatics / Artificial Intelligence and Natural Language Processing
Theses on a related topic
-
Comparison of methods for clustering convolutional neural network intercomputation values with respect to explainability
Adrián Bindas -
Explaining convolutional neural network using clustering methods
Adam Bajger -
Modelling small-RNA binding using Convolutional Neural Networks
Eva Klimentová -
implement classification for traffic signs using convolutional neural network
Mohamad Abdulrahman -
Bankruptcy prediction with explainable machine learning methods
Munkhnaran Tsogoo -
Google Translate and eTranslate: Neural Machine Translation Comparative Analysis
Ondřej Mičola -
Comparison of methods for clustering convolutional neural network intercomputation values with respect to explainability
Adrián Bindas -
Explaining convolutional neural network using clustering methods
Adam Bajger