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Enhancing transferability of foliar trait retrieval models: A comparative analysis of transfer learning strategies and domain shift characterization.

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Title: Enhancing transferability of foliar trait retrieval models: A comparative analysis of transfer learning strategies and domain shift characterization.
Authors: Huang, Yurong1, Liu, Nanfeng1, liunf3@mail.sysu.edu.cn, Chen, Wenqian1, Tan, Wei1, Deng, Yujia1, Wang, Zhihui2, Chlus, Adam3, Shen, Jian4, Townsend, Philip A.3
Source: Remote Sensing of Environment; May2026, Vol. 337, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 192193721
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Enhancing transferability of foliar trait retrieval models: A comparative analysis of transfer learning strategies and domain shift characterization.
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  Data: <searchLink fieldCode="JN" term="%22Remote+Sensing+of+Environment%22">Remote Sensing of Environment</searchLink>; May2026, Vol. 337, pN.PAG-N.PAG, 1p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=192193721
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.rse.2026.115336
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      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: N.PAG
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      – TitleFull: Enhancing transferability of foliar trait retrieval models: A comparative analysis of transfer learning strategies and domain shift characterization.
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            NameFull: Huang, Yurong
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            NameFull: Liu, Nanfeng
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            – D: 01
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              Text: May2026
              Type: published
              Y: 2026
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              Value: 337
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            – TitleFull: Remote Sensing of Environment
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