Please use this identifier to cite or link to this item:
https://elib.bsu.by/handle/123456789/306248| Title: | Compressing a convolution neural network based on quantization |
| Authors: | Pertsau, Dmitry Lukashevich, Marina Kupryianava, Dziana |
| Keywords: | ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Кибернетика ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика |
| Issue Date: | 2023 |
| Publisher: | Minsk : BSU |
| Citation: | Pattern Recognition and Information Processing (PRIP’2023). Artificial Universe: New Horisont : Proceedings of the 16 th International Conference, Belarus, Minsk, October 17–19, 2023 / Belarusian State University : eds. A. Nedzved, A. Belotserkovsky. – Minsk : BSU, 2023. – Pp. 269-272. |
| Abstract: | Modern deep neural network models contain a large number of parameters and have a significant size. In this paper we experimentally investigate approaches to compression of convolutional neural network. The results showing the efficiency of quantization of the model while maintaining high accuracy are obtained |
| URI: | https://elib.bsu.by/handle/123456789/306248 |
| ISBN: | 978-985-881-522-6 |
| Licence: | info:eu-repo/semantics/openAccess |
| Appears in Collections: | 2023. Pattern Recognition and Information Processing (PRIP’2023). Artificial Intelliverse: Expanding Horizons |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 269-272.pdf | 440,46 kB | Adobe PDF | View/Open |
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