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https://dspace.ncfu.ru/handle/20.500.12258/12082
Название: | Automatic system for evaluating the quality of the display of goods in a smart store based on cascading neural networks |
Авторы: | Talalaeva, J. Талалаева, Ю. Kuchukov, V. A. Кучуков, В. А. Kuchukova, E. A. Кучукова, Е. А. Vashchenko, I. S. Ващенко, И. С. Nazarov, A. S. Назаров, А. С. |
Ключевые слова: | Neural networks;Product layout;Semantic segmentation;Smart store;Video surveillance systems;Quality control |
Дата публикации: | 2020 |
Издатель: | Institute of Electrical and Electronics Engineers Inc. |
Библиографическое описание: | Talalaeva, J., Kuchukov, V., Kuchukova, E., Vashchenko, I., Nazarov, A. Automatic System for Evaluating the Quality of the Display of Goods in a Smart Store Based on Cascading Neural Networks // Proceedings of the 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, EIConRus 2020. - 2020. - Номер статьи 9039266. - Pages 530-532 |
Источник: | Proceedings of the 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, EIConRus 2020 |
Краткий осмотр (реферат): | In a new smart store, profit depends on the quality of the goods displayed on the shelf. If there is a product, but it is not laid out on shelves, the store suffers losses. In the paper, a control system is being developed for the timely display of goods on store shelves and for tracking in real-time the voids formed. To implement an automatic system for assessing the quality of filling store shelves with goods, we used cascading neural networks that performed two roles: a segmentation and a classifier, supplemented by an algorithmic solution to identify areas of potential voids. To train the classifier using the new algorithm, a training sample of 30 thousand images was created, 3 thousand images were used for validation, quality control on 10 thousand images. The proposed algorithm allowed us to obtain a quality of 96.7%. The developed system for assessing the quality of goods laying out on store shelves allows real-time assessment of the condition of shelves |
URI (Унифицированный идентификатор ресурса): | http://hdl.handle.net/20.500.12258/12082 |
Располагается в коллекциях: | Статьи, проиндексированные в SCOPUS, WOS |
Файлы этого ресурса:
Файл | Размер | Формат | |
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scopusresults 1253 .pdf Доступ ограничен | 626.23 kB | Adobe PDF | Просмотреть/Открыть |
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