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	<title>media forensics &#8211; BIOENGINEER.ORG</title>
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		<title>Hybrid AI Learns to Spot Deepfakes Without Sharing Sensitive Data</title>
		<link>https://bioengineer.org/hybrid-ai-learns-to-spot-deepfakes-without-sharing-sensitive-data/</link>
		
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		<pubDate>Wed, 07 Oct 2026 14:06:13 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[convolutional neural network]]></category>
		<category><![CDATA[deepfake detection]]></category>
		<category><![CDATA[domain generalization]]></category>
		<category><![CDATA[federated learning]]></category>
		<category><![CDATA[Hybrid models]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[media forensics]]></category>
		<category><![CDATA[non-IID data]]></category>
		<category><![CDATA[privacy-preserving AI]]></category>
		<category><![CDATA[statistical heterogeneity]]></category>
		<category><![CDATA[synthetic media]]></category>
		<category><![CDATA[vision transformer]]></category>
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					<description><![CDATA[Researchers have developed FedHybrid-ViT, a privacy-preserving framework that fuses convolutional and transformer models within federated learning to detect deepfakes across heterogeneous data sources, achieving an AUC of 0.925.]]></description>
		
		
		
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