Target identification method, target identification apparatus, terminal device and target identification system
The invention provides an online automatic deep learning-based target identification method and apparatus, a terminal device and a target identification system. The method comprises the steps of collecting image data in real time; by utilizing a stored first classifier, performing target identificat...
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creator | DAI YIRUO |
description | The invention provides an online automatic deep learning-based target identification method and apparatus, a terminal device and a target identification system. The method comprises the steps of collecting image data in real time; by utilizing a stored first classifier, performing target identification on the collected image data to generate image data with a category label, wherein the category label comprises a target category and a target posterior probability; when the target posterior probability meets a predetermined storage condition, performing storage as a training sample according to the target category; and when a predetermined starting condition is met, starting online deep learning processing to obtain a third classifier, and updating the stored first classifier by using the obtained third classifier. By adopting the method, high-accuracy target identification can be realized.
本发明提供了基于在线自动深度学习的目标识别方法、目标识别装置、终端设备和目标识别系统。其中,该方法包括:实时采集图像数据;利用存储的第分类器,对采集到的图像数据进行目标识别,以生成带有类别标签的图像数据,类别标签包含目标类别以及目标后验概率; |
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本发明提供了基于在线自动深度学习的目标识别方法、目标识别装置、终端设备和目标识别系统。其中,该方法包括:实时采集图像数据;利用存储的第分类器,对采集到的图像数据进行目标识别,以生成带有类别标签的图像数据,类别标签包含目标类别以及目标后验概率;</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; HANDLING RECORD CARRIERS ; PHYSICS ; PRESENTATION OF DATA ; RECOGNITION OF DATA ; RECORD CARRIERS</subject><creationdate>2017</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20171031&DB=EPODOC&CC=CN&NR=107305636A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,309,781,886,25568,76551</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20171031&DB=EPODOC&CC=CN&NR=107305636A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>DAI YIRUO</creatorcontrib><title>Target identification method, target identification apparatus, terminal device and target identification system</title><description>The invention provides an online automatic deep learning-based target identification method and apparatus, a terminal device and a target identification system. The method comprises the steps of collecting image data in real time; by utilizing a stored first classifier, performing target identification on the collected image data to generate image data with a category label, wherein the category label comprises a target category and a target posterior probability; when the target posterior probability meets a predetermined storage condition, performing storage as a training sample according to the target category; and when a predetermined starting condition is met, starting online deep learning processing to obtain a third classifier, and updating the stored first classifier by using the obtained third classifier. By adopting the method, high-accuracy target identification can be realized.
本发明提供了基于在线自动深度学习的目标识别方法、目标识别装置、终端设备和目标识别系统。其中,该方法包括:实时采集图像数据;利用存储的第分类器,对采集到的图像数据进行目标识别,以生成带有类别标签的图像数据,类别标签包含目标类别以及目标后验概率;</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>HANDLING RECORD CARRIERS</subject><subject>PHYSICS</subject><subject>PRESENTATION OF DATA</subject><subject>RECOGNITION OF DATA</subject><subject>RECORD CARRIERS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2017</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNi70KwjAURrM4iPoOca9QCbazlIqTU_dySb7qheaH5Cr49jo4Kjid4ZyzVHGgfIVodgjCE1sSjkF7yC26SstXSylRJrmXd4DsOdCsHR5soSm4H1N5FoFfq8VEc8Hmw5XanvqhO--Q4oiSyCJAxu6yr1tTHxrTHM0_zQuA10PV</recordid><startdate>20171031</startdate><enddate>20171031</enddate><creator>DAI YIRUO</creator><scope>EVB</scope></search><sort><creationdate>20171031</creationdate><title>Target identification method, target identification apparatus, terminal device and target identification system</title><author>DAI YIRUO</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN107305636A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2017</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>HANDLING RECORD CARRIERS</topic><topic>PHYSICS</topic><topic>PRESENTATION OF DATA</topic><topic>RECOGNITION OF DATA</topic><topic>RECORD CARRIERS</topic><toplevel>online_resources</toplevel><creatorcontrib>DAI YIRUO</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>DAI YIRUO</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Target identification method, target identification apparatus, terminal device and target identification system</title><date>2017-10-31</date><risdate>2017</risdate><abstract>The invention provides an online automatic deep learning-based target identification method and apparatus, a terminal device and a target identification system. The method comprises the steps of collecting image data in real time; by utilizing a stored first classifier, performing target identification on the collected image data to generate image data with a category label, wherein the category label comprises a target category and a target posterior probability; when the target posterior probability meets a predetermined storage condition, performing storage as a training sample according to the target category; and when a predetermined starting condition is met, starting online deep learning processing to obtain a third classifier, and updating the stored first classifier by using the obtained third classifier. By adopting the method, high-accuracy target identification can be realized.
本发明提供了基于在线自动深度学习的目标识别方法、目标识别装置、终端设备和目标识别系统。其中,该方法包括:实时采集图像数据;利用存储的第分类器,对采集到的图像数据进行目标识别,以生成带有类别标签的图像数据,类别标签包含目标类别以及目标后验概率;</abstract><oa>free_for_read</oa></addata></record> |
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language | chi ; eng |
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subjects | CALCULATING COMPUTING COUNTING HANDLING RECORD CARRIERS PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS |
title | Target identification method, target identification apparatus, terminal device and target identification system |
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