Return to search

Metody hlubokého učení pro zpracování obrazů / Deep learning methods for image processing

This master‘s thesis deals with the Deep Learning methods for image recognition tasks from the first methods to the modern ones. The main focus is on convolutional neural nets based models for classification, detection and image segmentation. These methods are used for practical implemetation – counting passing cars on video from traffic camera. After several test of available models, the YOLOv2 architecture was chosen and retrained on own dataset. The application also includes the addition of the SORT tracking algorithm.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:361733
Date January 2017
CreatorsKřenek, Jakub
ContributorsChmelík, Jiří, Kolář, Radim
PublisherVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií
Source SetsCzech ETDs
LanguageCzech
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

Page generated in 0.0019 seconds