ПРИНЦИПЫ ОРГАНИЗАЦИИ И АНАЛИЗ ПОДХОДОВ К ПОВЫШЕНИЮ ТОЧНОСТИ ПОВТОРНОЙ ИДЕНТИФИКАЦИИ ЛЮДЕЙ В РАСПРЕДЕЛЕННЫХ СИСТЕМАХ ВИДЕОНАБЛЮДЕНИЯ

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Просмотров аннотации: 212
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pdf (rus)
Опубликован: май 12, 2022
DOI: https://doi.org/10.52928/2070-1624-2022-38-4-13-25
Ключевые слова:
повторная идентификация человека, сверточные нейронные сети, скорость обучения, размер пакета person re-identification, convolutional neural networks, learning rate, batch size
Выпуск
№ 4 (2022)
Раздел
Информатика, вычислительная техника и управление

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С. А. ИГНАТЬЕВА
Полоцкий государственный университет
https://orcid.org/0000-0002-9780-5731

Аннотация

Приведена классификация существующих систем повторной идентификации по таким критериям, как тип системы, количество и вид запросов, время работы. Рассмотрена общая схема, отражающая основной принцип работы систем повторной идентификации, а также основные подходы и методы для решения этой задачи с использованием сверточных нейронных сетей. Выполнено исследование существующих способов повышения точности работы алгоритмов и систем повторной идентификации. Проведен анализ влияния выбора гиперпараметров при обучении сверточных нейронных сетей на эффективность и динамику обучения алгоритма повторной идентификации.

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Как цитировать
ИГНАТЬЕВА, С. А. (2022). ПРИНЦИПЫ ОРГАНИЗАЦИИ И АНАЛИЗ ПОДХОДОВ К ПОВЫШЕНИЮ ТОЧНОСТИ ПОВТОРНОЙ ИДЕНТИФИКАЦИИ ЛЮДЕЙ В РАСПРЕДЕЛЕННЫХ СИСТЕМАХ ВИДЕОНАБЛЮДЕНИЯ. Вестник Полоцкого государственного университета. Серия С. Фундаментальные науки, (4), 13-25. https://doi.org/10.52928/2070-1624-2022-38-4-13-25
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Это произведение доступно по лицензии Creative Commons «Attribution» («Атрибуция») 4.0 Всемирная.

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