Implementation of a CNN based object counting algorithm on bi-i cellular vision system
Object counting has been used in many areas such as medical and industrial applications. It is a challenging problem to count the target objects in high speed. It is useful to implement image processing applications using the high capability computational power offered by Cellular Neural Network typ...
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| creator | Sevgen, S. Karabiber, F. Yucel, E. Arik, S. |
| description | Object counting has been used in many areas such as medical and industrial applications. It is a challenging problem to count the target objects in high speed. It is useful to implement image processing applications using the high capability computational power offered by Cellular Neural Network type analog processor named as ACE16k. In this paper, we implement an efficient object counting algorithm working on ACE16k chip. Our results have proved that the proposed algorithm can count objects on a given image rapidly and accurately. |
| doi_str_mv | 10.1109/ELECO.2009.5355280 |
| format | Conference Proceeding |
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Our results have proved that the proposed algorithm can count objects on a given image rapidly and accurately.</description><identifier>ISBN: 142445106X</identifier><identifier>ISBN: 9781424451067</identifier><identifier>EISBN: 9789944898188</identifier><identifier>EISBN: 994489818X</identifier><identifier>DOI: 10.1109/ELECO.2009.5355280</identifier><language>eng</language><publisher>IEEE</publisher><subject>Application software ; Biomedical engineering ; Cellular neural networks ; Computer vision ; Humans ; Image processing ; Machine vision ; Power engineering and energy ; Power engineering computing ; Signal processing algorithms</subject><ispartof>2009 International Conference on Electrical and Electronics Engineering - ELECO 2009, 2009, p.II-394-II-397</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5355280$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5355280$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Sevgen, S.</creatorcontrib><creatorcontrib>Karabiber, F.</creatorcontrib><creatorcontrib>Yucel, E.</creatorcontrib><creatorcontrib>Arik, S.</creatorcontrib><title>Implementation of a CNN based object counting algorithm on bi-i cellular vision system</title><title>2009 International Conference on Electrical and Electronics Engineering - ELECO 2009</title><addtitle>ELECO</addtitle><description>Object counting has been used in many areas such as medical and industrial applications. 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Our results have proved that the proposed algorithm can count objects on a given image rapidly and accurately.</description><subject>Application software</subject><subject>Biomedical engineering</subject><subject>Cellular neural networks</subject><subject>Computer vision</subject><subject>Humans</subject><subject>Image processing</subject><subject>Machine vision</subject><subject>Power engineering and energy</subject><subject>Power engineering computing</subject><subject>Signal processing algorithms</subject><isbn>142445106X</isbn><isbn>9781424451067</isbn><isbn>9789944898188</isbn><isbn>994489818X</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNp9jsGqwjAURCMi-NT-gG7uD1iTmmiyLhUF0Y2IO0nrVSNJI0184N-r4NrZzOIMhyFkyGjKGFWTYl3k2zSjVKViKkQmaYskai6V4lwqyaRskx7jGeeC0dmhS5IQbvQdLrK5on9kv3J3iw7rqKPxNfgzaMg3Gyh1wBP48oZVhMo_6mjqC2h78Y2JVwfvbWnGBiq09mF1A_8mfAThGSK6AemctQ2YfLtPRotily_HBhGP98Y43TyP38vT3_QFMoJD2w</recordid><startdate>200911</startdate><enddate>200911</enddate><creator>Sevgen, S.</creator><creator>Karabiber, F.</creator><creator>Yucel, E.</creator><creator>Arik, S.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200911</creationdate><title>Implementation of a CNN based object counting algorithm on bi-i cellular vision system</title><author>Sevgen, S. ; Karabiber, F. ; Yucel, E. ; Arik, S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_53552803</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Application software</topic><topic>Biomedical engineering</topic><topic>Cellular neural networks</topic><topic>Computer vision</topic><topic>Humans</topic><topic>Image processing</topic><topic>Machine vision</topic><topic>Power engineering and energy</topic><topic>Power engineering computing</topic><topic>Signal processing algorithms</topic><toplevel>online_resources</toplevel><creatorcontrib>Sevgen, S.</creatorcontrib><creatorcontrib>Karabiber, F.</creatorcontrib><creatorcontrib>Yucel, E.</creatorcontrib><creatorcontrib>Arik, S.</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 Electronic Library (IEL)</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>Sevgen, S.</au><au>Karabiber, F.</au><au>Yucel, E.</au><au>Arik, S.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Implementation of a CNN based object counting algorithm on bi-i cellular vision system</atitle><btitle>2009 International Conference on Electrical and Electronics Engineering - ELECO 2009</btitle><stitle>ELECO</stitle><date>2009-11</date><risdate>2009</risdate><spage>II-394</spage><epage>II-397</epage><pages>II-394-II-397</pages><isbn>142445106X</isbn><isbn>9781424451067</isbn><eisbn>9789944898188</eisbn><eisbn>994489818X</eisbn><abstract>Object counting has been used in many areas such as medical and industrial applications. It is a challenging problem to count the target objects in high speed. It is useful to implement image processing applications using the high capability computational power offered by Cellular Neural Network type analog processor named as ACE16k. In this paper, we implement an efficient object counting algorithm working on ACE16k chip. Our results have proved that the proposed algorithm can count objects on a given image rapidly and accurately.</abstract><pub>IEEE</pub><doi>10.1109/ELECO.2009.5355280</doi></addata></record> |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Application software Biomedical engineering Cellular neural networks Computer vision Humans Image processing Machine vision Power engineering and energy Power engineering computing Signal processing algorithms |
| title | Implementation of a CNN based object counting algorithm on bi-i cellular vision system |
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