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	<title>diversified cropping systems &#8211; BIOENGINEER.ORG</title>
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		<title>Self-supervised AI learns to predict crop yields without labels</title>
		<link>https://bioengineer.org/self-supervised-ai-learns-to-predict-crop-yields-without-labels/</link>
		
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		<pubDate>Sat, 17 Oct 2026 03:39:30 +0000</pubDate>
				<category><![CDATA[Agriculture]]></category>
		<category><![CDATA[across]]></category>
		<category><![CDATA[crop]]></category>
		<category><![CDATA[crop yield prediction]]></category>
		<category><![CDATA[diversified cropping systems]]></category>
		<category><![CDATA[drone imagery]]></category>
		<category><![CDATA[learning]]></category>
		<category><![CDATA[precision agriculture]]></category>
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		<category><![CDATA[Self-supervised]]></category>
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		<category><![CDATA[yield]]></category>
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					<description><![CDATA[A neural network trained on unlabeled drone imagery of lupine, maize, soybean, and sunflower taught itself to distinguish crop types and management practices, then predicted yields with competitive accuracy and greater robustness than conventional supervised models.]]></description>
		
		
		
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