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	<title>StarNet &#8211; BIOENGINEER.ORG</title>
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		<title>Enhanced YOLOv8-pose network reads tennis actions and body poses from a single image</title>
		<link>https://bioengineer.org/enhanced-yolov8-pose-network-reads-tennis-actions-and-body-poses-from-a-single-image/</link>
		
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		<pubDate>Sun, 18 Oct 2026 16:30:43 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[attention module]]></category>
		<category><![CDATA[Computer Vision]]></category>
		<category><![CDATA[deep learning]]></category>
		<category><![CDATA[enhanced]]></category>
		<category><![CDATA[human pose estimation]]></category>
		<category><![CDATA[keypoint detection]]></category>
		<category><![CDATA[network]]></category>
		<category><![CDATA[real-time inference]]></category>
		<category><![CDATA[sports analytics]]></category>
		<category><![CDATA[StarNet]]></category>
		<category><![CDATA[tennis action classification]]></category>
		<category><![CDATA[YOLOv8-Pose]]></category>
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					<description><![CDATA[A research team has enhanced YOLOv8-Pose with a StarNet backbone, motion-relevant attention, and a composite keypoint loss to jointly classify tennis actions and estimate 17 body keypoints from single images, achieving 0.975 Pose AP50, 0.990 action accuracy, and 51.7 FPS on consumer GPU hardware.]]></description>
		
		
		
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