| Форма представления | Статьи в зарубежных журналах и сборниках |
| Год публикации | 2020 |
| Язык | английский |
|
Каюмов Зуфар Дамирович, автор
Мосин Сергей Геннадьевич, автор
Тумаков Дмитрий Николаевич, автор
|
| Библиографическое описание на языке оригинала |
Kayumov Z, Tumakov D, Mosin S., Combined Convolutional and Perceptron Neural Networks for Handwritten Digits Recognition//2020 22th International Conference on Digital Signal Processing and its Applications, DSPA 2020. - 2020. - Vol., Is.. - Art. № 9213301. |
| Аннотация |
The use of a combination of a convolutional neural network and multilayer perceptrons for recognizing handwritten digits is considered. Recognition is carried out by two sets of networks following each other. The first neural network selects two digits with maximum activation functions. Depending on the winners, the following network is activated (multilayer perceptron), which selects one digit from two. The proposed algorithm is tested on the data from MNIST. The recognition error is 0.75%. Obtained results demonstrate that the minimum error with this approach is 0.68%, and the accuracy of the F-metric is about 0.99 for each digit. The main feature of the proposed solution is dealt with the fact that the proposed cascaded combination of neural networks provides a sufficiently high accuracy with a simple architecture. |
| Ключевые слова |
handwritten digits, recognition, hierarchical convolutional neural network, MNIST |
| Название журнала |
2020 22th International Conference on Digital Signal Processing and its Applications, DSPA 2020
|
| URL |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85094597199&doi=10.1109%2fDSPA48919.2020.9213301&partnerID=40&md5=ef648da1f9071d6742ea52a7d886dfe1 |
| Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на эту карточку |
https://repository.kpfu.ru/?p_id=242052 |
Полная запись метаданных  |
| Поле DC |
Значение |
Язык |
| dc.contributor.author |
Каюмов Зуфар Дамирович |
ru_RU |
| dc.contributor.author |
Мосин Сергей Геннадьевич |
ru_RU |
| dc.contributor.author |
Тумаков Дмитрий Николаевич |
ru_RU |
| dc.date.accessioned |
2020-01-01T00:00:00Z |
ru_RU |
| dc.date.available |
2020-01-01T00:00:00Z |
ru_RU |
| dc.date.issued |
2020 |
ru_RU |
| dc.identifier.citation |
Kayumov Z, Tumakov D, Mosin S., Combined Convolutional and Perceptron Neural Networks for Handwritten Digits Recognition//2020 22th International Conference on Digital Signal Processing and its Applications, DSPA 2020. - 2020. - Vol., Is.. - Art. № 9213301. |
ru_RU |
| dc.identifier.uri |
https://repository.kpfu.ru/?p_id=242052 |
ru_RU |
| dc.description.abstract |
2020 22th International Conference on Digital Signal Processing and its Applications, DSPA 2020 |
ru_RU |
| dc.description.abstract |
The use of a combination of a convolutional neural network and multilayer perceptrons for recognizing handwritten digits is considered. Recognition is carried out by two sets of networks following each other. The first neural network selects two digits with maximum activation functions. Depending on the winners, the following network is activated (multilayer perceptron), which selects one digit from two. The proposed algorithm is tested on the data from MNIST. The recognition error is 0.75%. Obtained results demonstrate that the minimum error with this approach is 0.68%, and the accuracy of the F-metric is about 0.99 for each digit. The main feature of the proposed solution is dealt with the fact that the proposed cascaded combination of neural networks provides a sufficiently high accuracy with a simple architecture. |
ru_RU |
| dc.language.iso |
ru |
ru_RU |
| dc.subject |
handwritten digits |
ru_RU |
| dc.subject |
recognition |
ru_RU |
| dc.subject |
hierarchical convolutional neural network |
ru_RU |
| dc.subject |
MNIST |
ru_RU |
| dc.title |
Combined Convolutional and Perceptron Neural Networks for Handwritten Digits Recognition |
ru_RU |
| dc.type |
Статьи в зарубежных журналах и сборниках |
ru_RU |
|
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