Практичні аспекти формування навчальних/тестових вибірок для згорткових нейронних мереж
The most common approaches to assessing the quality of training neural networks in the context of the problem of "small training sets" are analyzed. A review of the code implementation of the most universal approaches and ways of extending training/testing samples is carried out. The logic...
Збережено в:
| Дата: | 2022 |
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| Автори: | , , , |
| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
Vinnytsia National Technical University
2022
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| Теми: | |
| Онлайн доступ: | https://oeipt.vntu.edu.ua/index.php/oeipt/article/view/611 |
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| Назва журналу: | Optoelectronic Information-Power Technologies |
Репозитарії
Optoelectronic Information-Power Technologies| Резюме: | The most common approaches to assessing the quality of training neural networks in the context of the problem of "small training sets" are analyzed. A review of the code implementation of the most universal approaches and ways of extending training/testing samples is carried out. The logic of the work of STN-module is analyzed. It can be inserted into existing convolutional architectures, giving neural networks the ability to actively spatially transform feature maps, conditional on the feature map itself, without any extra training supervision or modification to the optimization process. |
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