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	<title>多實例學習 Archives &#8212; MATLAB Number ONE</title>
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	<title>多實例學習 Archives &#8212; MATLAB Number ONE</title>
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		<title>Real-time Object Tracking via Online Discriminative Feature Selection</title>
		<link>https://matlab1.com/shop/matlab-code/real-time-object-tracking-via-online-discriminative-feature-selection/</link>
					<comments>https://matlab1.com/shop/matlab-code/real-time-object-tracking-via-online-discriminative-feature-selection/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Mon, 07 May 2018 11:41:33 +0000</pubDate>
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					<description><![CDATA[<p>Most tracking-by-detection algorithms train discriminative classifiers to separate target objects from their surrounding background. In this setting, noisy samples are likely to be included when they are not properly sampled, thereby causing visual drift. The multiple instance learning (MIL) paradigm has been recently applied to alleviate this problem. However, important prior information of instance labels and the most correct positive instance (i.e., [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/real-time-object-tracking-via-online-discriminative-feature-selection/">Real-time Object Tracking via Online Discriminative Feature Selection</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>Robust object tracking via active feature selection</title>
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					<comments>https://matlab1.com/shop/matlab-code/robust-object-tracking-via-active-feature-selection/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Sun, 15 Apr 2018 13:43:50 +0000</pubDate>
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					<description><![CDATA[<p>In this project, we proposed a robust tracker based on an online discriminative appearance model. In order to design a robust appearance model, we developed an online active feature selection (AFS) approach via minimizing a Fishier information criterion. We showed that the features selected by our proposed online AFS boosting algorithm are much more informative and discriminative than those selected by [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/robust-object-tracking-via-active-feature-selection/">Robust object tracking via active feature selection</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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