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Fusing Spatial and Temporal Features Extracted Using Convolutional Neural Networks and Gated Recurrent Units for Improved Deepfake Detection.

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Title: Fusing Spatial and Temporal Features Extracted Using Convolutional Neural Networks and Gated Recurrent Units for Improved Deepfake Detection.
Authors: Abdulrahman Abdulhamed, Mohamed1 mohammed@uobasrah.edu.iq, Noori Hashim, Asaad2
Source: Iraqi Journal for Electrical & Electronic Engineering. Jun2026, Vol. 22 Issue 1, p218-226. 9p.
Database: Academic Search Ultimate
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  Data: <searchLink fieldCode="JN" term="%22Iraqi+Journal+for+Electrical+%26+Electronic+Engineering%22">Iraqi Journal for Electrical & Electronic Engineering</searchLink>. Jun2026, Vol. 22 Issue 1, p218-226. 9p.
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        Value: 10.37917/ijeee.22.1.20
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      – Code: eng
        Text: English
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        PageCount: 9
        StartPage: 218
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      – TitleFull: Fusing Spatial and Temporal Features Extracted Using Convolutional Neural Networks and Gated Recurrent Units for Improved Deepfake Detection.
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              Text: Jun2026
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              Y: 2026
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