| DC Field | Value | Language |
|---|
| dc.contributor.author | Ihnatsyeva, S. | - |
| dc.contributor.author | Bohush, R. | - |
| dc.contributor.author | Ablameyko, S. | - |
| dc.date.accessioned | 2021-11-04T08:59:26Z | - |
| dc.date.available | 2021-11-04T08:59:26Z | - |
| dc.date.issued | 2021 | - |
| dc.identifier.citation | Ihnatsyeva, S. Joint Dataset for CNN-based Person Re-identification / Ihnatsyeva S., Bohush R., Ablameyko S. // Pattern Recognition and Information Processing (PRIP'2021) = Распознавание образов и обработка информации (2021) : Proceedings of the 15th International Conference, 21–24 Sept. 2021, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2021. – P. 33–37. | ru_RU |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/45798 | - |
| dc.description.abstract | In this paper, we propose a joint dataset for person re-identification task that includes the existing public datasets CUHK02, CUHK03, Market, Duke, LPW and our collected PolReID. We investigate the training dataset size and composition effect on the re-identification accuracy. We carried out a number of experiments with different size of dataset to solve re-identification task. The results of experiments are presented. | ru_RU |
| dc.language.iso | en | ru_RU |
| dc.publisher | UIIP NASB | ru_RU |
| dc.subject | материалы конференций | ru_RU |
| dc.subject | conference proceedings | ru_RU |
| dc.subject | large-scale dataset | ru_RU |
| dc.subject | cross domain | ru_RU |
| dc.subject | convolution neural network | ru_RU |
| dc.subject | PolReID dataset | ru_RU |
| dc.title | Joint Dataset for CNN-based Person Re-identification | ru_RU |
| dc.type | Статья | ru_RU |
| Appears in Collections: | Pattern Recognition and Information Processing (PRIP'2021) = Распознавание образов и обработка информации (2021)
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