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Identification of shipping signals with few-shot learning: A distribution-aware approach.

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Title: Identification of shipping signals with few-shot learning: A distribution-aware approach.
Authors: Kim BK; Department of Artificial Intelligence Convergence, Pukyong National University, Busan, Korea., Cho S; Department of Ocean Science, University of Science & Technology (UST), Busan, Korea.; Sea Power Reinforcement· Security Research Department, Korea Institute of Ocean Science & Technology, Busan, Korea., Kim S; Sea Power Reinforcement· Security Research Department, Korea Institute of Ocean Science & Technology, Busan, Korea., Kim H; Department of Ocean Science, University of Science & Technology (UST), Busan, Korea.; Sea Power Reinforcement· Security Research Department, Korea Institute of Ocean Science & Technology, Busan, Korea., Jin YJ; Department of Artificial Intelligence Convergence, Pukyong National University, Busan, Korea., Choi HT; Department of Artificial Intelligence Convergence, Pukyong National University, Busan, Korea., Chang WD; Department of Artificial Intelligence Convergence, Pukyong National University, Busan, Korea.
Source: PloS one [PLoS One] 2026 Jul 09; Vol. 21 (7), pp. e0352683. Date of Electronic Publication: 2026 Jul 09 (Print Publication: 2026).
Publication Type: Journal Article
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Identification of shipping signals with few-shot learning: A distribution-aware approach.
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  Data: <searchLink fieldCode="AU" term="%22Kim+BK%22">Kim BK</searchLink>; Department of Artificial Intelligence Convergence, Pukyong National University, Busan, Korea.<br /><searchLink fieldCode="AU" term="%22Cho+S%22">Cho S</searchLink>; Department of Ocean Science, University of Science & Technology (UST), Busan, Korea.; Sea Power Reinforcement· Security Research Department, Korea Institute of Ocean Science & Technology, Busan, Korea.<br /><searchLink fieldCode="AU" term="%22Kim+S%22">Kim S</searchLink>; Sea Power Reinforcement· Security Research Department, Korea Institute of Ocean Science & Technology, Busan, Korea.<br /><searchLink fieldCode="AU" term="%22Kim+H%22">Kim H</searchLink>; Department of Ocean Science, University of Science & Technology (UST), Busan, Korea.; Sea Power Reinforcement· Security Research Department, Korea Institute of Ocean Science & Technology, Busan, Korea.<br /><searchLink fieldCode="AU" term="%22Jin+YJ%22">Jin YJ</searchLink>; Department of Artificial Intelligence Convergence, Pukyong National University, Busan, Korea.<br /><searchLink fieldCode="AU" term="%22Choi+HT%22">Choi HT</searchLink>; Department of Artificial Intelligence Convergence, Pukyong National University, Busan, Korea.<br /><searchLink fieldCode="AU" term="%22Chang+WD%22">Chang WD</searchLink>; Department of Artificial Intelligence Convergence, Pukyong National University, Busan, Korea.
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  Data: <searchLink fieldCode="JN" term="%22101285081%22">PloS one</searchLink> [PLoS One] 2026 Jul 09; Vol. 21 (7), pp. e0352683. <i>Date of Electronic Publication: </i>2026 Jul 09 (<i>Print Publication: </i>2026).
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        Value: 10.1371/journal.pone.0352683
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              Text: 2026 Jul 09
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