Імпульсні нейронні мережі для задач класифікації зображень
| dc.contributor.advisor | Швай, Надія | |
| dc.contributor.author | Кравченко, Ілля | |
| dc.date.accessioned | 2022-01-17T21:14:18Z | |
| dc.date.available | 2022-01-17T21:14:18Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | This work is dedicated to the discussion of the main features of the classical fully-connected feed-forward Artificial Neural Network(ANN) and the Spiking Neural Network(SNN) based on their performance on the MNIST dataset and a few of its variations. Firstly, models’ architectures are discussed, then they are trained on the MNIST dataset. Finally, their performances are compared, and from the results of the experiment, the conclusion is stated. | uk_UA |
| dc.identifier.uri | https://ekmair.ukma.edu.ua/handle/123456789/22283 | |
| dc.language.iso | en | uk_UA |
| dc.status | first published | uk_UA |
| dc.subject | нейронні мережі | uk_UA |
| dc.subject | класифікація зображень | uk_UA |
| dc.subject | магістерська робота | uk_UA |
| dc.title | Імпульсні нейронні мережі для задач класифікації зображень | uk_UA |
| dc.type | Other | uk_UA |
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