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Deep Learning Object Detection Video Analysis to Determine Grain Boundary Defect Sink Efficacy in Ion Irradiated Specimens.

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Title: Deep Learning Object Detection Video Analysis to Determine Grain Boundary Defect Sink Efficacy in Ion Irradiated Specimens.
Authors: Mang, Emily H, Barnett, Annie K, Lech, Sebastian, Taheri, Mitra L
Source: Microscopy and microanalysis: the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada 2024 Supplement; Vol. 30.
Journal Info: Publisher: Oxford University Press / USA ISSN: 1431-9276
Database: MEDLINE Ultimate
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  Data: Deep Learning Object Detection Video Analysis to Determine Grain Boundary Defect Sink Efficacy in Ion Irradiated Specimens.
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  Data: <searchLink fieldCode="JN" term="%229712707%22">Microscopy and microanalysis: the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada</searchLink> 2024 Supplement; Vol. 30.
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      – Type: doi
        Value: 10.1093/mam/ozae044.843
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      – Code: eng
        Text: English
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      – TitleFull: Deep Learning Object Detection Video Analysis to Determine Grain Boundary Defect Sink Efficacy in Ion Irradiated Specimens.
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            NameFull: Mang, Emily H
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            NameFull: Barnett, Annie K
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            NameFull: Lech, Sebastian
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              Text: 2024 Supplement
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              Y: 2024
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              Value: 1435-8115
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              Value: 30
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            – TitleFull: Microscopy and microanalysis: the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada
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