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STEM Image Analysis Based on Deep Learning: Identification of Vacancy Defects and Polymorphs of MoS2.
Lee, Kihyun; Park, Jinsub; Choi, Soyeon; Lee, Yangjin; Lee, Sol; Jung, Joowon; Lee, Jong-Young; Ullah, Farman; Tahir, Zeeshan; Kim, Yong Soo; Lee, Gwan-Hyoung; Kim, Kwanpyo.
Affiliation
  • Lee K; Department of Physics, Yonsei University, Seoul 03722, Korea.
  • Park J; Department of Physics, Yonsei University, Seoul 03722, Korea.
  • Choi S; Department of Physics, Yonsei University, Seoul 03722, Korea.
  • Lee Y; Department of Physics, Yonsei University, Seoul 03722, Korea.
  • Lee S; Center for Nanomedicine, Institute for Basic Science (IBS), Seoul 03722, Korea.
  • Jung J; Department of Physics, Yonsei University, Seoul 03722, Korea.
  • Lee JY; Center for Nanomedicine, Institute for Basic Science (IBS), Seoul 03722, Korea.
  • Ullah F; Department of Physics, Yonsei University, Seoul 03722, Korea.
  • Tahir Z; Department of Material Science and Engineering, Seoul National University, Seoul 08826, Korea.
  • Kim YS; Department of Physics and Energy Harvest Storage Research Center, University of Ulsan, Ulsan 44610, Korea.
  • Lee GH; Department of Physics and Energy Harvest Storage Research Center, University of Ulsan, Ulsan 44610, Korea.
  • Kim K; Department of Physics and Energy Harvest Storage Research Center, University of Ulsan, Ulsan 44610, Korea.
Nano Lett ; 22(12): 4677-4685, 2022 06 22.
Article in En | MEDLINE | ID: mdl-35674452
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Deep Learning Type of study: Diagnostic_studies / Guideline Language: En Journal: Nano Lett Year: 2022 Type: Article
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Deep Learning Type of study: Diagnostic_studies / Guideline Language: En Journal: Nano Lett Year: 2022 Type: Article