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Image objects detection based on boosting neural network
This paper discusses the problem of object area detection of video frames. The goal is to design a pixel accurate detector for grass, which could be used for object adaptive video enhancement. A boosting neural network is used for creating such a detector. The resulted detector uses both textural fe...
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| container_end_page | 211 |
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| container_start_page | 207 |
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| creator | Ningqing Liang Hegt, H Mladenov, V M |
| description | This paper discusses the problem of object area detection of video frames. The goal is to design a pixel accurate detector for grass, which could be used for object adaptive video enhancement. A boosting neural network is used for creating such a detector. The resulted detector uses both textural features and color features of the frames. |
| doi_str_mv | 10.1109/NEUREL.2010.5644063 |
| format | conference_proceeding |
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The goal is to design a pixel accurate detector for grass, which could be used for object adaptive video enhancement. A boosting neural network is used for creating such a detector. The resulted detector uses both textural features and color features of the frames.</description><identifier>ISBN: 1424488214</identifier><identifier>ISBN: 9781424488216</identifier><identifier>EISBN: 9781424488209</identifier><identifier>EISBN: 9781424488193</identifier><identifier>EISBN: 1424488192</identifier><identifier>EISBN: 1424488206</identifier><identifier>DOI: 10.1109/NEUREL.2010.5644063</identifier><language>eng</language><publisher>IEEE</publisher><subject>Artificial neural networks ; Boosting ; boosting neural network ; Classification algorithms ; feature ; Feature extraction ; grass ; Image color analysis ; Pixel ; Training</subject><ispartof>10th Symposium on Neural Network Applications in Electrical Engineering, 2010, p.207-211</ispartof><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://ieeexplore.ieee.org/document/5644063$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5644063$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Ningqing Liang</creatorcontrib><creatorcontrib>Hegt, H</creatorcontrib><creatorcontrib>Mladenov, V M</creatorcontrib><title>Image objects detection based on boosting neural network</title><title>10th Symposium on Neural Network Applications in Electrical Engineering</title><addtitle>NEUREL</addtitle><description>This paper discusses the problem of object area detection of video frames. The goal is to design a pixel accurate detector for grass, which could be used for object adaptive video enhancement. A boosting neural network is used for creating such a detector. The resulted detector uses both textural features and color features of the frames.</description><subject>Artificial neural networks</subject><subject>Boosting</subject><subject>boosting neural network</subject><subject>Classification algorithms</subject><subject>feature</subject><subject>Feature extraction</subject><subject>grass</subject><subject>Image color analysis</subject><subject>Pixel</subject><subject>Training</subject><isbn>1424488214</isbn><isbn>9781424488216</isbn><isbn>9781424488209</isbn><isbn>9781424488193</isbn><isbn>1424488192</isbn><isbn>1424488206</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1j91KAzEUhCMiqHWfoDd5ga3Jyf-llFULi0Jpr0tizpbUdlc2K-LbG7HOzTdzOAwMIXPOFpwzd__SbNdNuwBWDkpLybS4IJUzlkuQ0lpg7pLc_gcur0mV84EVKTDSwA2xq5PfIx3CAd-mTCNOhWnoafAZI_01w5Cn1O9pj5-jPxZMX8P4fkeuOn_MWJ05I9vHZrN8rtvXp9Xyoa0TF0rUAbWKKigAZBijd0ExCUx1FhwXRbp8YPGeoQ1gXCiwKDrojDZeixmZ__UmRNx9jOnkx-_deaz4AaS6R9o</recordid><startdate>201009</startdate><enddate>201009</enddate><creator>Ningqing Liang</creator><creator>Hegt, H</creator><creator>Mladenov, V M</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201009</creationdate><title>Image objects detection based on boosting neural network</title><author>Ningqing Liang ; Hegt, H ; Mladenov, V M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i1353-be65d5b522e0edda9b504205f829133336be6e291a0e8b279be8b8e3f2f767a63</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Artificial neural networks</topic><topic>Boosting</topic><topic>boosting neural network</topic><topic>Classification algorithms</topic><topic>feature</topic><topic>Feature extraction</topic><topic>grass</topic><topic>Image color analysis</topic><topic>Pixel</topic><topic>Training</topic><toplevel>online_resources</toplevel><creatorcontrib>Ningqing Liang</creatorcontrib><creatorcontrib>Hegt, H</creatorcontrib><creatorcontrib>Mladenov, V M</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE/IET Electronic Library</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ningqing Liang</au><au>Hegt, H</au><au>Mladenov, V M</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Image objects detection based on boosting neural network</atitle><btitle>10th Symposium on Neural Network Applications in Electrical Engineering</btitle><stitle>NEUREL</stitle><date>2010-09</date><risdate>2010</risdate><spage>207</spage><epage>211</epage><pages>207-211</pages><isbn>1424488214</isbn><isbn>9781424488216</isbn><eisbn>9781424488209</eisbn><eisbn>9781424488193</eisbn><eisbn>1424488192</eisbn><eisbn>1424488206</eisbn><abstract>This paper discusses the problem of object area detection of video frames. The goal is to design a pixel accurate detector for grass, which could be used for object adaptive video enhancement. A boosting neural network is used for creating such a detector. The resulted detector uses both textural features and color features of the frames.</abstract><pub>IEEE</pub><doi>10.1109/NEUREL.2010.5644063</doi><tpages>5</tpages><oa>free_for_read</oa></addata></record> |
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| identifier | ISBN: 1424488214 |
| ispartof | 10th Symposium on Neural Network Applications in Electrical Engineering, 2010, p.207-211 |
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| language | eng |
| recordid | cdi_ieee_primary_5644063 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Artificial neural networks Boosting boosting neural network Classification algorithms feature Feature extraction grass Image color analysis Pixel Training |
| title | Image objects detection based on boosting neural network |
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