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	<title>terrain change detection &#8211; BIOENGINEER.ORG</title>
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		<title>Attention-Boosted PointNet++ Strips Vegetation from Mountain LiDAR to Build Sharper Terrain Maps</title>
		<link>https://bioengineer.org/attention-boosted-pointnet-strips-vegetation-from-mountain-lidar-to-build-sharper-terrain-maps/</link>
		
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		<pubDate>Wed, 28 Oct 2026 01:35:30 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Attention Mechanism]]></category>
		<category><![CDATA[deep learning]]></category>
		<category><![CDATA[digital elevation model]]></category>
		<category><![CDATA[ground filtering]]></category>
		<category><![CDATA[LiDAR]]></category>
		<category><![CDATA[model scaling]]></category>
		<category><![CDATA[OpenGF dataset]]></category>
		<category><![CDATA[point cloud filtering]]></category>
		<category><![CDATA[PointNet++]]></category>
		<category><![CDATA[remote sensing]]></category>
		<category><![CDATA[terrain change detection]]></category>
		<category><![CDATA[Three Sisters Peak]]></category>
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					<description><![CDATA[An enhanced PointNet++ with attention mechanisms and model scaling reaches up to 96.26 percent accuracy in separating ground from vegetation in complex slope LiDAR data and cuts DEM errors against traditional filters.]]></description>
		
		
		
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