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Hyperspectral anomaly detection based on spatial-spectral feature fusion autoencoder.

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Title: Hyperspectral anomaly detection based on spatial-spectral feature fusion autoencoder.
Authors: Zhang, Zhimin1, zhangzhimin@uest.edu.gr, Ma, Chengzhen1,2, mczseed@163.com, Teng, Xiao1, txiao_cc@163.com, Ning, Huansheng3, ninghuansheng@ustb.edu.cn, Mao, Lingfeng3, lingfengmao@ustb.edu.cn, Zhang, Dan1, zhangdan_706@163.com
Source: Neurocomputing; May2026, Vol. 678, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 192259339
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=192259339
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      – Type: doi
        Value: 10.1016/j.neucom.2026.133162
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      – Code: eng
        Text: English
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      – TitleFull: Hyperspectral anomaly detection based on spatial-spectral feature fusion autoencoder.
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            NameFull: Zhang, Zhimin
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            NameFull: Ma, Chengzhen
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            NameFull: Teng, Xiao
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            NameFull: Mao, Lingfeng
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            – D: 14
              M: 05
              Text: May2026
              Type: published
              Y: 2026
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