Automobile identification method based on Centernet
The invention discloses an automobile identification method based on the Centernet. The automobile identification method comprises the following steps: S1, acquiring and collecting original image data; s2, classifying the original images into a training set, a verification set and a test set; respec...
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creator | CAI RUNXUAN FANG ZHIJUN |
description | The invention discloses an automobile identification method based on the Centernet. The automobile identification method comprises the following steps: S1, acquiring and collecting original image data; s2, classifying the original images into a training set, a verification set and a test set; respectively carrying out enhancement processing on the training set, the verification set and the test set to obtain an enhanced training set, an enhanced verification set and an enhanced test set; s3, building a network structure based on the Centernet; s4, standardizing the Center network structure byadopting Group Normalization, taking a Radam optimizer as an optimization method of network training, and carrying out iterative training to obtain a trained Centernet network structure; and S5, verifying and testing the trained Centernet network structure by using the enhanced verification set and the enhanced test set. According to the method, on the basis of vehicle types and position features,the features of the botto |
format | Patent |
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The automobile identification method comprises the following steps: S1, acquiring and collecting original image data; s2, classifying the original images into a training set, a verification set and a test set; respectively carrying out enhancement processing on the training set, the verification set and the test set to obtain an enhanced training set, an enhanced verification set and an enhanced test set; s3, building a network structure based on the Centernet; s4, standardizing the Center network structure byadopting Group Normalization, taking a Radam optimizer as an optimization method of network training, and carrying out iterative training to obtain a trained Centernet network structure; and S5, verifying and testing the trained Centernet network structure by using the enhanced verification set and the enhanced test set. According to the method, on the basis of vehicle types and position features,the features of the botto</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; HANDLING RECORD CARRIERS ; PHYSICS ; PRESENTATION OF DATA ; RECOGNITION OF DATA ; RECORD CARRIERS</subject><creationdate>2020</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=20200825&DB=EPODOC&CC=CN&NR=111582213A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,777,882,25545,76296</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20200825&DB=EPODOC&CC=CN&NR=111582213A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>CAI RUNXUAN</creatorcontrib><creatorcontrib>FANG ZHIJUN</creatorcontrib><title>Automobile identification method based on Centernet</title><description>The invention discloses an automobile identification method based on the Centernet. The automobile identification method comprises the following steps: S1, acquiring and collecting original image data; s2, classifying the original images into a training set, a verification set and a test set; respectively carrying out enhancement processing on the training set, the verification set and the test set to obtain an enhanced training set, an enhanced verification set and an enhanced test set; s3, building a network structure based on the Centernet; s4, standardizing the Center network structure byadopting Group Normalization, taking a Radam optimizer as an optimization method of network training, and carrying out iterative training to obtain a trained Centernet network structure; and S5, verifying and testing the trained Centernet network structure by using the enhanced verification set and the enhanced test set. According to the method, on the basis of vehicle types and position features,the features of the botto</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</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>2020</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZDB2LC3Jz81PysxJVchMSc0ryUzLTE4syczPU8hNLcnIT1FISixOTVEA8p2BsqlFeaklPAysaYk5xam8UJqbQdHNNcTZQze1ID8-tbggMTkVqCre2c_Q0NDUwsjI0NjRmBg1ABdPLIo</recordid><startdate>20200825</startdate><enddate>20200825</enddate><creator>CAI RUNXUAN</creator><creator>FANG ZHIJUN</creator><scope>EVB</scope></search><sort><creationdate>20200825</creationdate><title>Automobile identification method based on Centernet</title><author>CAI RUNXUAN ; FANG ZHIJUN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN111582213A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2020</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</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>CAI RUNXUAN</creatorcontrib><creatorcontrib>FANG ZHIJUN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>CAI RUNXUAN</au><au>FANG ZHIJUN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Automobile identification method based on Centernet</title><date>2020-08-25</date><risdate>2020</risdate><abstract>The invention discloses an automobile identification method based on the Centernet. The automobile identification method comprises the following steps: S1, acquiring and collecting original image data; s2, classifying the original images into a training set, a verification set and a test set; respectively carrying out enhancement processing on the training set, the verification set and the test set to obtain an enhanced training set, an enhanced verification set and an enhanced test set; s3, building a network structure based on the Centernet; s4, standardizing the Center network structure byadopting Group Normalization, taking a Radam optimizer as an optimization method of network training, and carrying out iterative training to obtain a trained Centernet network structure; and S5, verifying and testing the trained Centernet network structure by using the enhanced verification set and the enhanced test set. According to the method, on the basis of vehicle types and position features,the features of the botto</abstract><oa>free_for_read</oa></addata></record> |
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language | chi ; eng |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING HANDLING RECORD CARRIERS PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS |
title | Automobile identification method based on Centernet |
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