Please use this identifier to cite or link to this item:
https://elib.psu.by/handle/123456789/33689
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chen, H. | - |
dc.contributor.author | Ihnatsyeva, S. | - |
dc.contributor.author | Bohush, R. | - |
dc.contributor.author | Ablameyko, S. | - |
dc.date.accessioned | 2022-10-04T06:49:12Z | - |
dc.date.available | 2022-10-04T06:49:12Z | - |
dc.date.issued | 2022 | - |
dc.identifier.citation | Chen, H., Ihnatsyeva, S., Bohush, R. et al. Choice of Activation Function in Convolutional Neural Networks for Person Re-Identification in Video Surveillance Systems. Program Comput Soft 48, 312–321 (2022). https://doi.org/10.1134/S0361768822050036 | ru_RU |
dc.identifier.uri | https://elib.psu.by/handle/123456789/33689 | - |
dc.description.abstract | In this paper, we improve the accuracy of person re-identification in images obtained from distributed video surveillance systems by choosing activation functions for convolutional neural networks. The most popular activation functions used for object detection, namely, ReLU, Leaky-ReLU, PReLU, RReLU, ELU, SELU, GELU, Swish, and Mish, are analyzed based on the following metrics: Rank1, Rank5, Rank10, mAP, and training time. For feature extraction, ResNet-50, DenseNet-121, and DarkNet-53 architectures are employed. The experimental study is carried out on open datasets Market1501 and PolReID. The accuracy of person re-identification is assessed after thrice-repeated training and testing with different activation functions, neural network architectures, and datasets by averaging the values of the selected metrics. | ru_RU |
dc.language.iso | en | ru_RU |
dc.publisher | Springer | ru_RU |
dc.title | Choice of Activation Function in Convolutional Neural Networks for Person Re-Identification in Video Surveillance Systems | ru_RU |
dc.type | Article | ru_RU |
dc.identifier.doi | 10.1134/S0361768822050036 | - |
Appears in Collections: | Публикации в Scopus и Web of Science Машинное обучение. Обработкой изображений и видео. Интеллектуальные системы. Информационная безопасность |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
312–321.pdf | 140.02 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.