Airport flight area target real-time detection method based on multi-scale feature decoupling
The invention discloses an airport flight area target real-time detection method based on multi-scale feature decoupling, and the method comprises the steps: 1, obtaining an airport flight area monitoring video, and constructing an airport flight area target detection data set; 2, constructing a mul...
Gespeichert in:
| Hauptverfasser: | , , , , , , , , |
|---|---|
| Format: | Patent |
| Sprache: | chi ; eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | QI MEIBIN ZHU WEI WANG XIAO JI XIANYANG HU DI ZHUANG SHUO DONG XIAOSHU XIN FUHAO XING ZHIQIANG |
| description | The invention discloses an airport flight area target real-time detection method based on multi-scale feature decoupling, and the method comprises the steps: 1, obtaining an airport flight area monitoring video, and constructing an airport flight area target detection data set; 2, constructing a multi-scale feature fusion module to realize detection of targets of different scales; 3, classifying and positioning tasks in target detection are decoupled, and a learning network based on feature decoupling is constructed; and 4, adding a learning network based on feature decoupling and a multi-scale feature fusion module into a YOLOv5 target detection network, and training and optimizing a target detection model in combination with a loss function. According to the method, shallow detail information and deep semantic information are aggregated by using the multi-scale feature fusion module, the detection capability of targets of different scales is enhanced, classification and positioning tasks are decoupled by us |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN116206257A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN116206257A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN116206257A3</originalsourceid><addsrcrecordid>eNqNikEKwjAUBbtxIeodvgco2IrtuhTFlSu3Ur7JaxpIk5D83l8LHsDVzMBsi1dnUwxJaHTWTEKcwCScDIS-6kqxM0hDoMQGTzNkCprenKFp7cWJLbNiBxrBsqT1VmGJznqzLzYju4zDj7vieLs--3uJGAbkyAoeMvSPqmrqU1Nf2u78z_MB7us8MQ</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Airport flight area target real-time detection method based on multi-scale feature decoupling</title><source>esp@cenet</source><creator>QI MEIBIN ; ZHU WEI ; WANG XIAO ; JI XIANYANG ; HU DI ; ZHUANG SHUO ; DONG XIAOSHU ; XIN FUHAO ; XING ZHIQIANG</creator><creatorcontrib>QI MEIBIN ; ZHU WEI ; WANG XIAO ; JI XIANYANG ; HU DI ; ZHUANG SHUO ; DONG XIAOSHU ; XIN FUHAO ; XING ZHIQIANG</creatorcontrib><description>The invention discloses an airport flight area target real-time detection method based on multi-scale feature decoupling, and the method comprises the steps: 1, obtaining an airport flight area monitoring video, and constructing an airport flight area target detection data set; 2, constructing a multi-scale feature fusion module to realize detection of targets of different scales; 3, classifying and positioning tasks in target detection are decoupled, and a learning network based on feature decoupling is constructed; and 4, adding a learning network based on feature decoupling and a multi-scale feature fusion module into a YOLOv5 target detection network, and training and optimizing a target detection model in combination with a loss function. According to the method, shallow detail information and deep semantic information are aggregated by using the multi-scale feature fusion module, the detection capability of targets of different scales is enhanced, classification and positioning tasks are decoupled by us</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ; PHYSICS</subject><creationdate>2023</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=20230602&DB=EPODOC&CC=CN&NR=116206257A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25544,76293</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230602&DB=EPODOC&CC=CN&NR=116206257A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>QI MEIBIN</creatorcontrib><creatorcontrib>ZHU WEI</creatorcontrib><creatorcontrib>WANG XIAO</creatorcontrib><creatorcontrib>JI XIANYANG</creatorcontrib><creatorcontrib>HU DI</creatorcontrib><creatorcontrib>ZHUANG SHUO</creatorcontrib><creatorcontrib>DONG XIAOSHU</creatorcontrib><creatorcontrib>XIN FUHAO</creatorcontrib><creatorcontrib>XING ZHIQIANG</creatorcontrib><title>Airport flight area target real-time detection method based on multi-scale feature decoupling</title><description>The invention discloses an airport flight area target real-time detection method based on multi-scale feature decoupling, and the method comprises the steps: 1, obtaining an airport flight area monitoring video, and constructing an airport flight area target detection data set; 2, constructing a multi-scale feature fusion module to realize detection of targets of different scales; 3, classifying and positioning tasks in target detection are decoupled, and a learning network based on feature decoupling is constructed; and 4, adding a learning network based on feature decoupling and a multi-scale feature fusion module into a YOLOv5 target detection network, and training and optimizing a target detection model in combination with a loss function. According to the method, shallow detail information and deep semantic information are aggregated by using the multi-scale feature fusion module, the detection capability of targets of different scales is enhanced, classification and positioning tasks are decoupled by us</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNikEKwjAUBbtxIeodvgco2IrtuhTFlSu3Ur7JaxpIk5D83l8LHsDVzMBsi1dnUwxJaHTWTEKcwCScDIS-6kqxM0hDoMQGTzNkCprenKFp7cWJLbNiBxrBsqT1VmGJznqzLzYju4zDj7vieLs--3uJGAbkyAoeMvSPqmrqU1Nf2u78z_MB7us8MQ</recordid><startdate>20230602</startdate><enddate>20230602</enddate><creator>QI MEIBIN</creator><creator>ZHU WEI</creator><creator>WANG XIAO</creator><creator>JI XIANYANG</creator><creator>HU DI</creator><creator>ZHUANG SHUO</creator><creator>DONG XIAOSHU</creator><creator>XIN FUHAO</creator><creator>XING ZHIQIANG</creator><scope>EVB</scope></search><sort><creationdate>20230602</creationdate><title>Airport flight area target real-time detection method based on multi-scale feature decoupling</title><author>QI MEIBIN ; ZHU WEI ; WANG XIAO ; JI XIANYANG ; HU DI ; ZHUANG SHUO ; DONG XIAOSHU ; XIN FUHAO ; XING ZHIQIANG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN116206257A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>QI MEIBIN</creatorcontrib><creatorcontrib>ZHU WEI</creatorcontrib><creatorcontrib>WANG XIAO</creatorcontrib><creatorcontrib>JI XIANYANG</creatorcontrib><creatorcontrib>HU DI</creatorcontrib><creatorcontrib>ZHUANG SHUO</creatorcontrib><creatorcontrib>DONG XIAOSHU</creatorcontrib><creatorcontrib>XIN FUHAO</creatorcontrib><creatorcontrib>XING ZHIQIANG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>QI MEIBIN</au><au>ZHU WEI</au><au>WANG XIAO</au><au>JI XIANYANG</au><au>HU DI</au><au>ZHUANG SHUO</au><au>DONG XIAOSHU</au><au>XIN FUHAO</au><au>XING ZHIQIANG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Airport flight area target real-time detection method based on multi-scale feature decoupling</title><date>2023-06-02</date><risdate>2023</risdate><abstract>The invention discloses an airport flight area target real-time detection method based on multi-scale feature decoupling, and the method comprises the steps: 1, obtaining an airport flight area monitoring video, and constructing an airport flight area target detection data set; 2, constructing a multi-scale feature fusion module to realize detection of targets of different scales; 3, classifying and positioning tasks in target detection are decoupled, and a learning network based on feature decoupling is constructed; and 4, adding a learning network based on feature decoupling and a multi-scale feature fusion module into a YOLOv5 target detection network, and training and optimizing a target detection model in combination with a loss function. According to the method, shallow detail information and deep semantic information are aggregated by using the multi-scale feature fusion module, the detection capability of targets of different scales is enhanced, classification and positioning tasks are decoupled by us</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | chi ; eng |
| recordid | cdi_epo_espacenet_CN116206257A |
| source | esp@cenet |
| subjects | CALCULATING COMPUTING COUNTING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS |
| title | Airport flight area target real-time detection method based on multi-scale feature decoupling |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-27T16%3A52%3A20IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=QI%20MEIBIN&rft.date=2023-06-02&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN116206257A%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |