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FDPNet: Deep forgery detection by leveraging multi-scale self-forgery images generating.

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Title: FDPNet: Deep forgery detection by leveraging multi-scale self-forgery images generating.
Authors: Li, Boyang1, macchiato4ever@gmail.com, Zhao, Huihuang1,2, happyday.huihuang@gmail.com, Li, Leyi1, llyhlg72027@gmail.com
Source: Journal of Supercomputing; Apr2025, Vol. 81 Issue 6, p1-24, 24p
Database: Applied Science & Technology Source
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PubType: Academic Journal
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  Data: FDPNet: Deep forgery detection by leveraging multi-scale self-forgery images generating.
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  Data: <searchLink fieldCode="AU" term="%22Li%2C+Boyang%22">Li, Boyang</searchLink><relatesTo>1</relatesTo>, <i>macchiato4ever@gmail.com</i><br /><searchLink fieldCode="AU" term="%22Zhao%2C+Huihuang%22">Zhao, Huihuang</searchLink><relatesTo>1,2</relatesTo>, <i>happyday.huihuang@gmail.com</i><br /><searchLink fieldCode="AU" term="%22Li%2C+Leyi%22">Li, Leyi</searchLink><relatesTo>1</relatesTo>, <i>llyhlg72027@gmail.com</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Supercomputing%22">Journal of Supercomputing</searchLink>; Apr2025, Vol. 81 Issue 6, p1-24, 24p
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      – Type: doi
        Value: 10.1007/s11227-025-07229-3
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      – Code: eng
        Text: English
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        PageCount: 24
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      – TitleFull: FDPNet: Deep forgery detection by leveraging multi-scale self-forgery images generating.
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            NameFull: Li, Boyang
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            NameFull: Zhao, Huihuang
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              Text: Apr2025
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              Y: 2025
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              Value: 81
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