| DC Field | Value | Language |
|---|
| dc.contributor.author | Tang, Yi | - |
| dc.contributor.author | Gourinovitch, A. | - |
| dc.coverage.spatial | Минск | - |
| dc.date.accessioned | 2022-12-05T11:00:10Z | - |
| dc.date.available | 2022-12-05T11:00:10Z | - |
| dc.date.issued | 2022 | - |
| dc.identifier.citation | Tang ,Yi Small object detection method / Yi. Tang, A. Gourinovitch // Информационные технологии и системы 2022 (ИТС 2022) = Information Technologies and Systems 2022 (ITS 2022) : материалы Международной научной конференции, Минск, 23 ноября 2022 / Белорусский государственный университет информатики и радиоэлектроники ; редкол.: Л. Ю. Шилин [и др.]. – Минск : БГУИР, 2022. – С. 169–170. | ru_RU |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/49286 | - |
| dc.description.abstract | In computer vision, significant advances have been made on object detection with the rapid development of deep convolutional neural networks (CNN)/ When it comes to small objects? the accuracy of deep learning methdods is low. | ru_RU |
| dc.language.iso | en | ru_RU |
| dc.publisher | БГУИР | ru_RU |
| dc.subject | материалы конференций | ru_RU |
| dc.subject | controvolutional neural networks | ru_RU |
| dc.subject | object detection | ru_RU |
| dc.subject | pattern recognition | ru_RU |
| dc.subject | feature pyramid network | ru_RU |
| dc.title | Small object detection method | ru_RU |
| dc.type | Article | ru_RU |
| Appears in Collections: | ИТС 2022
|
