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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.
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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  Data: 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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  Data: <searchLink fieldCode="AU" term="%22Jeong+JM%22">Jeong JM</searchLink>; 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.<br /><searchLink fieldCode="AU" term="%22Ra+M%22">Ra M</searchLink>; LightVision Inc. 20 Seongsuil-ro 12-gil, Seongdong-gu Seoul 04793 Republic of Korea trizmaster@gmail.com.<br /><searchLink fieldCode="AU" term="%22Jeong+J%22">Jeong J</searchLink>; LightVision Inc. 20 Seongsuil-ro 12-gil, Seongdong-gu Seoul 04793 Republic of Korea trizmaster@gmail.com.<br /><searchLink fieldCode="AU" term="%22Lee+W%22">Lee W</searchLink>; 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.
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  Data: <searchLink fieldCode="JN" term="%22101581657%22">RSC advances</searchLink> [RSC Adv] 2024 Jun 10; Vol. 14 (26), pp. 18489-18500. <i>Date of Electronic Publication: </i>2024 Jun 10 (<i>Print Publication: </i>2024).
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Royal+Society+of+Chemistry%22">Royal Society of Chemistry </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101581657 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Internet <i>ISSN: </i>2046-2069 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2220462069%22">20462069 </searchLink><i>NLM ISO Abbreviation: </i>RSC Adv <i>Subsets: </i>PubMed not MEDLINE
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1039/d3ra08939h
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      – Code: eng
        Text: English
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        StartPage: 18489
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      – TitleFull: 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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            NameFull: Jeong JM
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            NameFull: Ra M
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            NameFull: Jeong J
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            – D: 10
              M: 06
              Text: 2024 Jun 10
              Type: published
              Y: 2024
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              Value: 2046-2069
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              Value: 14
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            – TitleFull: RSC advances
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