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. |
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| 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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| ISSN: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0352683 |
