Performance of a deep convolutional neural network to classify crystal structures using selected area electron beam diffraction patterns containing lattice defect information.
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| Title: | Performance of a deep convolutional neural network to classify crystal structures using selected area electron beam diffraction patterns containing lattice defect information. |
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| Authors: | Jeong JM; Dept. of Materials Convergence and System Engineering, Changwon National University 20 Changwondaehak-ro Changwon-si Gyeongsangnam-do 51140 Republic of Korea woonglee@changwon.ac.kr., Ra M; LightVision Inc. 20 Seongsuil-ro 12-gil, Seongdong-gu Seoul 04793 Republic of Korea trizmaster@gmail.com., Jeong J; LightVision Inc. 20 Seongsuil-ro 12-gil, Seongdong-gu Seoul 04793 Republic of Korea trizmaster@gmail.com., Lee W; Dept. of Materials Convergence and System Engineering, Changwon National University 20 Changwondaehak-ro Changwon-si Gyeongsangnam-do 51140 Republic of Korea woonglee@changwon.ac.kr.; School of Materials Science and Engineering, Changwon National University 20 Changwondaehak-ro Changwon-si Gyeongsangnam-do 51140 Republic of Korea. |
| Source: | RSC advances [RSC Adv] 2024 Jun 10; Vol. 14 (26), pp. 18489-18500. Date of Electronic Publication: 2024 Jun 10 (Print Publication: 2024). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Royal Society of Chemistry Country of Publication: England NLM ID: 101581657 Publication Model: eCollection Cited Medium: Internet ISSN: 2046-2069 (Electronic) Linking ISSN: 20462069 NLM ISO Abbreviation: RSC Adv Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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