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	<title>DinoV3 &#8211; BIOENGINEER.ORG</title>
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		<title>AI Ensemble of Vision Transformers Detects Voice Disorders With Record Accuracy</title>
		<link>https://bioengineer.org/ai-ensemble-of-vision-transformers-detects-voice-disorders-with-record-accuracy/</link>
		
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		<pubDate>Wed, 07 Oct 2026 19:36:42 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[boosting]]></category>
		<category><![CDATA[deep learning]]></category>
		<category><![CDATA[DinoV3]]></category>
		<category><![CDATA[ensemble learning]]></category>
		<category><![CDATA[EVA-02]]></category>
		<category><![CDATA[laryngitis]]></category>
		<category><![CDATA[MaxViT]]></category>
		<category><![CDATA[mel-spectrogram]]></category>
		<category><![CDATA[model calibration]]></category>
		<category><![CDATA[Parkinson’s disease]]></category>
		<category><![CDATA[vision transformer]]></category>
		<category><![CDATA[voice disorders]]></category>
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					<description><![CDATA[Researchers in Kerala combined DinoV3, EVA-02, and MaxViT vision transformers into a boosted, calibrated voting ensemble that detects six laryngeal and neurological voice disorders with 86.84 percent accuracy.]]></description>
		
		
		
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