Using Computer Vision and Deep Learning for Nanoparticle Recognition on Scanning Probe Microscopy Images: Modified U-net Approach Conference Abstracts
| Conference |
2020 Science and Artificial Intelligence Conference 14-15 Nov 2020 , Novosibirsk |
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| Source | 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 Compilation, Novosibirsk State University. Novosibirsk.2020. |
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| Output data | Year: 2020, Article number : 9303184, Pages count : 4 DOI: 10.1109/S.A.I.ence50533.2020.9303184 | ||||||
| Tags | deep neural networks; particles recognition; scanning probe microscopy | ||||||
| Authors |
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| Affiliations |
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Funding (2)
| 1 | Ministry of Science and Higher Education of the Russian Federation | ГЗ-2017-2020 |
| 2 | The Ministry of Education and Science of the Russian Federation |
Abstract:
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.
Cite:
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
In compilation 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
In compilation 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
Dates:
| Published print: | Nov 14, 2020 |
Identifiers:
| Scopus: | 2-s2.0-85099564872 |
| OpenAlex: | W3113635397 |