The aim of the present work is to select a suitable object classification method for the recognition of one-handed finger alphabet characters. For this purpose, a sufficiently robust dataset has been created and is included in this work. The creation of the dataset is necessary for training the convolutional neural network. Further more, a suitable topology for data classification was found. The whole work is implemented using Python and the open-source library Keras was used.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:455694 |
| Date | January 2021 |
| Creators | Zbavitel, Tomáš |
| Contributors | Věchet, Stanislav, Krejsa, Jiří |
| Publisher | Vysoké učení technické v Brně. Fakulta strojního inženýrství |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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