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Compressive sensing reconstruction of hyperspectral images based on codec space‐spectrum joint dense residual network.

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Title: Compressive sensing reconstruction of hyperspectral images based on codec space‐spectrum joint dense residual network.
Authors: Xiao, Shuming1,2, Zhang, Ye1,2, yolanda@spirits.ai, Chang, Xuling1,2, Xu, Jiajia1,2
Source: IET Image Processing (Wiley-Blackwell); 2/28/2023, Vol. 17 Issue 3, p916-931, 16p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 161968597
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Compressive sensing reconstruction of hyperspectral images based on codec space‐spectrum joint dense residual network.
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  Data: <searchLink fieldCode="JN" term="%22IET+Image+Processing+%28Wiley-Blackwell%29%22">IET Image Processing (Wiley-Blackwell)</searchLink>; 2/28/2023, Vol. 17 Issue 3, p916-931, 16p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=161968597
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1049/ipr2.12682
    Languages:
      – Code: eng
        Text: English
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        PageCount: 16
        StartPage: 916
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      – TitleFull: Compressive sensing reconstruction of hyperspectral images based on codec space‐spectrum joint dense residual network.
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            NameFull: Xiao, Shuming
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            NameFull: Zhang, Ye
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            NameFull: Chang, Xuling
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            NameFull: Xu, Jiajia
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            – D: 28
              M: 02
              Text: 2/28/2023
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              Y: 2023
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              Value: 17
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          Titles:
            – TitleFull: IET Image Processing (Wiley-Blackwell)
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