Using Computer Vision and Deep Learning for Nanoparticle Recognition on Scanning Probe Microscopy Images: Modified U-net Approach Тезисы доклада
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2020 Science and Artificial Intelligence Conference 14-15 нояб. 2020 , Novosibirsk |
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| Сборник | 2020 Science and Artificial Intelligence conference (S.A.I.ence) : Proceedings of International virtual conference with A.I.-enabled reproducible scientific results with technical sponsorship from IEEE,14–15 November 2020, Novosibirsk, Russia Сборник, Novosibirsk State University. Novosibirsk.2020. |
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| Вых. Данные | Год: 2020, Номер статьи : 9303184, Страниц : 4 DOI: 10.1109/S.A.I.ence50533.2020.9303184 | ||||||
| Ключевые слова | deep neural networks; particles recognition; scanning probe microscopy | ||||||
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| Организации |
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Информация о финансировании (2)
| 1 | Министерство науки и высшего образования Российской Федерации (с 15 мая 2018) | ГЗ-2017-2020 |
| 2 | Министерство образования и науки Российской Федерации |
Реферат:
Particles characterization is a significant part of numerous studies in material sciences and engineering technologies. Microscopy images of materials containing particles are usually analyzed by operator with manual counting and measuring of particle sizing by a software ruler. Traditional automated image analyzing methods such as edge detection, segmentation, etc. are not universal, giving poor results on noisy pictures and need empirical fitted parameters. To realize automatic method of particles recognition on scanning tunneling microscopy (STM) data we used U-net and modified U-net neural networks, which was trained on ten STM images contained 1918 particles. Verification on 3 pictures with 695 particles showed mAP=0.12 for modified U-net neural network. © 2020 IEEE.
Библиографическая ссылка:
Liz M.F.
, Nartova A.V.
, Matveev A.V.
, Okunev A.G.
Using Computer Vision and Deep Learning for Nanoparticle Recognition on Scanning Probe Microscopy Images: Modified U-net Approach
В сборнике 2020 Science and Artificial Intelligence conference (S.A.I.ence) : Proceedings of International virtual conference with A.I.-enabled reproducible scientific results with technical sponsorship from IEEE,14–15 November 2020, Novosibirsk, Russia. – Novosibirsk State University., 2020. – C.13-16. DOI: 10.1109/S.A.I.ence50533.2020.9303184 Scopus OpenAlex
Using Computer Vision and Deep Learning for Nanoparticle Recognition on Scanning Probe Microscopy Images: Modified U-net Approach
В сборнике 2020 Science and Artificial Intelligence conference (S.A.I.ence) : Proceedings of International virtual conference with A.I.-enabled reproducible scientific results with technical sponsorship from IEEE,14–15 November 2020, Novosibirsk, Russia. – Novosibirsk State University., 2020. – C.13-16. DOI: 10.1109/S.A.I.ence50533.2020.9303184 Scopus OpenAlex
Даты:
| Опубликована в печати: | 14 нояб. 2020 г. |
Идентификаторы БД:
| Scopus: | 2-s2.0-85099564872 |
| OpenAlex: | W3113635397 |