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		<title>Deep learning system scores long jump technique and lifts student performance</title>
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		<pubDate>Mon, 26 Oct 2026 23:42:01 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[BiLSTM]]></category>
		<category><![CDATA[deep learning]]></category>
		<category><![CDATA[DeepSORT]]></category>
		<category><![CDATA[dynamic time warping]]></category>
		<category><![CDATA[intelligent teaching]]></category>
		<category><![CDATA[long jump]]></category>
		<category><![CDATA[motion assessment]]></category>
		<category><![CDATA[OpenPose]]></category>
		<category><![CDATA[physical education]]></category>
		<category><![CDATA[pose estimation]]></category>
		<category><![CDATA[sports technology]]></category>
		<category><![CDATA[YOLOv5]]></category>
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					<description><![CDATA[Researchers combined YOLOv5, DeepSORT, OpenPose, BiLSTM and Dynamic Time Warping into a long jump teaching system that scored take-off movements with 90.50 percent accuracy and helped students raise their overall jump scores by 15.63 points over eight weeks.]]></description>
		
		
		
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