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Improving SAM 2 for Agricultural Land Segmentation through Fine-Tuning, Point Prompt Augmentation, and Negative Prompt Calibration.

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Title: Improving SAM 2 for Agricultural Land Segmentation through Fine-Tuning, Point Prompt Augmentation, and Negative Prompt Calibration.
Authors: Budi, Yayang Setia1 yayang.setia.tif421@polban.ac.id, Al Jihad, Fardan1 fardan.al.tif421@polban.ac.id, Syakrani, Nurjannah1 nurjannahsy@jtk.polban.ac.id, Gelar, Trisna1 trisna.gelar@polban.ac.id, Sholahuddin, Muhammad Rizqi1 muhammad.rizqi@polban.ac.id, Lieharyani, Djoko Cahyo Utomo1 djoko.c.utomo@polban.ac.id
Source: Journal of Information Systems Engineering & Business Intelligence. Jun2026, Vol. 12 Issue 2, p210-222. 13p.
Database: Business Source Ultimate
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An: 195306469
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Improving SAM 2 for Agricultural Land Segmentation through Fine-Tuning, Point Prompt Augmentation, and Negative Prompt Calibration.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Information+Systems+Engineering+%26+Business+Intelligence%22">Journal of Information Systems Engineering & Business Intelligence</searchLink>. Jun2026, Vol. 12 Issue 2, p210-222. 13p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bsu&AN=195306469
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        Value: 10.20473/jisebi.12.2.210-222
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      – Code: eng
        Text: English
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        StartPage: 210
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      – TitleFull: Improving SAM 2 for Agricultural Land Segmentation through Fine-Tuning, Point Prompt Augmentation, and Negative Prompt Calibration.
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            NameFull: Al Jihad, Fardan
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              Text: Jun2026
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              Y: 2026
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