<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>通過自適應預測移動設備上初始搜索點的對象跟踪 Archives &#8212; MATLAB Number ONE</title>
	<atom:link href="https://matlab1.com/product-tag/%e9%80%9a%e9%81%8e%e8%87%aa%e9%81%a9%e6%87%89%e9%a0%90%e6%b8%ac%e7%a7%bb%e5%8b%95%e8%a8%ad%e5%82%99%e4%b8%8a%e5%88%9d%e5%a7%8b%e6%90%9c%e7%b4%a2%e9%bb%9e%e7%9a%84%e5%b0%8d%e8%b1%a1%e8%b7%9f%e8%b8%aa/feed/" rel="self" type="application/rss+xml" />
	<link>https://matlab1.com/product-tag/通過自適應預測移動設備上初始搜索點的對象跟踪/</link>
	<description>MATLAB Simulink &#124; Tutorial &#124; Code &#124; Project</description>
	<lastBuildDate>Fri, 03 Dec 2021 06:27:48 +0000</lastBuildDate>
	<language>en-GB</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	

<image>
	<url>https://matlab1.com/wp-content/uploads/2018/08/icon1-100x100.png</url>
	<title>通過自適應預測移動設備上初始搜索點的對象跟踪 Archives &#8212; MATLAB Number ONE</title>
	<link>https://matlab1.com/product-tag/通過自適應預測移動設備上初始搜索點的對象跟踪/</link>
	<width>32</width>
	<height>32</height>
</image> 
	<item>
		<title>Object tracking via adaptive prediction of initial search point on mobile devices</title>
		<link>https://matlab1.com/shop/java-code/object-tracking-via-adaptive-prediction-of-initial-search-point-on-mobile-devices/</link>
					<comments>https://matlab1.com/shop/java-code/object-tracking-via-adaptive-prediction-of-initial-search-point-on-mobile-devices/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Tue, 03 Apr 2018 08:33:41 +0000</pubDate>
				<guid isPermaLink="false">https://matlab1.com/?post_type=product&#038;p=4703</guid>

					<description><![CDATA[<p>Common feature tracking algorithms, such as SIFT and SURF, are fairly slow in runtime due to the processing of a large amount of external data. If the object is sufficiently small, outside noise may throw off the object detection device without prior knowledge. Machine learning, especially Markov chains, can use prior knowledge to turn a computationally expensive task into [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/java-code/object-tracking-via-adaptive-prediction-of-initial-search-point-on-mobile-devices/">Object tracking via adaptive prediction of initial search point on mobile devices</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
					<wfw:commentRss>https://matlab1.com/shop/java-code/object-tracking-via-adaptive-prediction-of-initial-search-point-on-mobile-devices/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
	</channel>
</rss>
