Particle Recognition on Transmission Electron Microscopy Images Using Computer Vision and Deep Learning for Catalytic Applications Научная публикация
| Журнал |
Catalysts
ISSN: 2073-4344 |
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| Вых. Данные | Год: 2022, Том: 12, Номер: 2, Номер статьи : 135, Страниц : 13 DOI: 10.3390/catal12020135 | ||||
| Ключевые слова | Deep neural networks; Particle recognition; Particles; Supported catalysts; Transmission electron microscopy | ||||
| Авторы |
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| Организации |
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Информация о финансировании (1)
| 1 | Российский научный фонд | 22-23-00951 |
Реферат:
Recognition and measuring particles on microscopy images is an important part of many scientific studies, including catalytic investigations. In this paper, we present the results of the application of deep learning to the automated recognition of nanoparticles deposited on porous supports (heterogeneous catalysts) on images obtained by transmission electron microscopy (TEM). The Cascade Mask-RCNN neural network was used. During the training, two types of objects were labeled on raw TEM images of ‘real’ catalysts: visible particles and overlapping particle projections. The trained neural network recognized nanoparticles in the test dataset with 0.71 precision and 0.72 recall for both classes of objects and 0.84 precision and 0.79 recall for visible particles. The developed model is integrated into the open-access web service ‘ParticlesNN’, which can be used by any researcher in the world. Instead of hours, TEM data processing per one image analysis is reduced to a maximum of a couple of minutes and the divergence of mean particle size determination is approximately 2% compared to manual analysis. The proposed tool encourages accelerating catalytic research and improving the objectivity and accuracy of analysis. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Библиографическая ссылка:
Nartova A.V.
, Mashukov M.Y.
, Astakhov R.R.
, Kudinov V.Y.
, Matveev A.V.
, Okunev A.G.
Particle Recognition on Transmission Electron Microscopy Images Using Computer Vision and Deep Learning for Catalytic Applications
Catalysts. 2022. V.12. N2. 135 :1-13. DOI: 10.3390/catal12020135 WOS Scopus РИНЦ CAPlusCA OpenAlex
Particle Recognition on Transmission Electron Microscopy Images Using Computer Vision and Deep Learning for Catalytic Applications
Catalysts. 2022. V.12. N2. 135 :1-13. DOI: 10.3390/catal12020135 WOS Scopus РИНЦ CAPlusCA OpenAlex
Даты:
| Поступила в редакцию: | 27 дек. 2021 г. |
| Принята к публикации: | 14 янв. 2022 г. |
| Опубликована online: | 22 янв. 2022 г. |
| Опубликована в печати: | 1 февр. 2022 г. |
Идентификаторы БД:
| Web of science: | WOS:000763698800001 |
| Scopus: | 2-s2.0-85123083971 |
| РИНЦ: | 48144540 |
| Chemical Abstracts: | 2022:570394 |
| Chemical Abstracts (print): | 178:102820 |
| OpenAlex: | W4283377556 |