Виявлення об’єктів в процесі розпізнавання зображень за допомогою трансформерів
Modern object detection methods in the image recognition process using transformer technology are analyzed. The various methods advantages and disadvantages are identified. An own network was created based on the DETR transformer from the FAIR team, and its operation was analyzed. A comparison of th...
Збережено в:
| Дата: | 2022 |
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| Автори: | , , |
| Формат: | Стаття |
| Мова: | Ukrainian |
| Опубліковано: |
Kamianets-Podilskyi National Ivan Ohiienko University
2022
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| Онлайн доступ: | http://mcm-tech.kpnu.edu.ua/article/view/269340 |
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| Назва журналу: | Mathematical and computer modelling. Series: Technical sciences |
Репозитарії
Mathematical and computer modelling. Series: Technical sciences| Резюме: | Modern object detection methods in the image recognition process using transformer technology are analyzed.
The various methods advantages and disadvantages are identified. An own network was created based on the DETR transformer from the FAIR team, and its operation was analyzed. A comparison of the transformer networks performance with optimized architectures of convolutional neural networks is made.
The cloud computing tools, graphics processors, Internet of Things clusters or embedded microprocessor systems were used in the research process.
To ensure high object detector accuracy and real-time detection results on different types of devices, an efficient object detector and model scaling technique are required.
The transformer model learning is illustrated step-by-step process. |
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