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		<title>Lightweight AI Network Brings Accurate Skin-Lesion Segmentation to Edge Devices</title>
		<link>https://bioengineer.org/lightweight-ai-network-brings-accurate-skin-lesion-segmentation-to-edge-devices/</link>
		
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		<pubDate>Mon, 05 Oct 2026 15:48:09 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Attention Mechanism]]></category>
		<category><![CDATA[cloud-edge computing]]></category>
		<category><![CDATA[Computer Vision]]></category>
		<category><![CDATA[deep learning]]></category>
		<category><![CDATA[Dice score]]></category>
		<category><![CDATA[image segmentation]]></category>
		<category><![CDATA[IoU]]></category>
		<category><![CDATA[ISIC 2018]]></category>
		<category><![CDATA[lightweight neural networks]]></category>
		<category><![CDATA[Medical Imaging]]></category>
		<category><![CDATA[model efficiency]]></category>
		<category><![CDATA[skin-lesion segmentation]]></category>
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					<description><![CDATA[Researchers have developed LMANet, a lightweight multiscale attention network that achieves high-accuracy skin-lesion segmentation with only 5.6 million parameters by splitting work between edge devices and the cloud.]]></description>
		
		
		
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