Automatic electron hologram acquisition of catalyst nanoparticles using particle detection with image processing and machine learning

Fumiaki Ichihashi, Akira Koyama, Tetsuya Akashi, Shoko Miyauchi, Kenichi Morooka, Hajime Hojo, Hisahiro Einaga, Yoshio Takahashi, Toshiaki Tanigaki, Hiroyuki Shinada, Yasukazu Murakami

研究成果: ジャーナルへの寄稿学術誌査読

抄録

To enable better statistical analysis of catalyst nanoparticles by high-resolution electron holography, we improved the particle detection accuracy of our previously developed automated hologram acquisition system by using an image classifier trained with machine learning. The detection accuracy of 83% was achieved with the small training data of just 232 images showing nanoparticles by utilizing transfer learning based on VGG16 to train the image classifier. Although the construction of training data generally requires much effort, the time needed to select the training data candidates was significantly shortened by utilizing a pattern matching technique. Experimental results showed that the high-resolution hologram acquisition efficiency was improved by factors of about 100 and 6 compared to a scan method and a pattern-matching-only method, respectively.

本文言語英語
論文番号064103
ジャーナルApplied Physics Letters
120
6
DOI
出版ステータス出版済み - 2月 7 2022

!!!All Science Journal Classification (ASJC) codes

  • 物理学および天文学(その他)

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