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Illumination correction of dyed fabrics method using the kernel extreme learning machine based on the improved Aquila Optimizer.

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Title: Illumination correction of dyed fabrics method using the kernel extreme learning machine based on the improved Aquila Optimizer.
Authors: Peng, Laihu1,2, Zhang, Xiaorong1, Li, Jianqiang2, wzcnljq@126.com, Ru, Xin1, Hu, Xudong1
Source: Textile Research Journal; Jul2025, Vol. 95 Issue 13/14, p1557-1575, 19p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 185388492
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Illumination correction of dyed fabrics method using the kernel extreme learning machine based on the improved Aquila Optimizer.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=185388492
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1177/00405175241269180
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 19
        StartPage: 1557
    Titles:
      – TitleFull: Illumination correction of dyed fabrics method using the kernel extreme learning machine based on the improved Aquila Optimizer.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Peng, Laihu
      – PersonEntity:
          Name:
            NameFull: Zhang, Xiaorong
      – PersonEntity:
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            NameFull: Li, Jianqiang
      – PersonEntity:
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            NameFull: Ru, Xin
      – PersonEntity:
          Name:
            NameFull: Hu, Xudong
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          Dates:
            – D: 01
              M: 07
              Text: Jul2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 00405175
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            – Type: volume
              Value: 95
            – Type: issue
              Value: 13/14
          Titles:
            – TitleFull: Textile Research Journal
              Type: main
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