Industrial meter identification method based on multi-frame vision

Industrial meter identification method based on multi-frame vision

The invention discloses an industrial meter identification method based on multi-frame vision. The industrial meter identification method comprises the following steps: 1, continuously shooting N photos towards a preset target near a preset shooting point by utilizing a shooting device; 2, extractin...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: BAI FAN, HUANG DINGJIANG
Format: Patent
Sprache:chi ; eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
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 BAI FAN
HUANG DINGJIANG
description The invention discloses an industrial meter identification method based on multi-frame vision. The industrial meter identification method comprises the following steps: 1, continuously shooting N photos towards a preset target near a preset shooting point by utilizing a shooting device; 2, extracting depth features of the N photos through the same set of convolutional neural networks to obtain feature tensors of N HxWxCs, wherein H is the height, W is the width, and C is the length; 3, respectively normalizing the characteristic tensors of the N HxWxCs into an intensity matrix of HxW by utilizing a trained full connection layer; and 4, normalizing each intensity matrix through softmax, and calculating the weighted sum of the characteristic tensors of each characteristic tensor HxWxC through weight to obtain N new vectors with the length of C as target characteristic vectors x '. According to the invention, the problems of meter identification failure and errors caused by accidental shooting factors are greatl
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN111507323A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN111507323A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN111507323A3</originalsourceid><addsrcrecordid>eNrjZHDyzEspLS4pykzMUchNLUktUshMSc0ryUzLTE4syczPAwlm5KcoJCUWp6YogPilOSWZumlFibmpCmWZxUAlPAysaYk5xam8UJqbQdHNNcTZQze1ID8-tbggMTk1L7Uk3tnP0NDQ1MDc2MjY0ZgYNQBwUTJV</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Industrial meter identification method based on multi-frame vision</title><source>esp@cenet</source><creator>BAI FAN ; HUANG DINGJIANG</creator><creatorcontrib>BAI FAN ; HUANG DINGJIANG</creatorcontrib><description>The invention discloses an industrial meter identification method based on multi-frame vision. The industrial meter identification method comprises the following steps: 1, continuously shooting N photos towards a preset target near a preset shooting point by utilizing a shooting device; 2, extracting depth features of the N photos through the same set of convolutional neural networks to obtain feature tensors of N HxWxCs, wherein H is the height, W is the width, and C is the length; 3, respectively normalizing the characteristic tensors of the N HxWxCs into an intensity matrix of HxW by utilizing a trained full connection layer; and 4, normalizing each intensity matrix through softmax, and calculating the weighted sum of the characteristic tensors of each characteristic tensor HxWxC through weight to obtain N new vectors with the length of C as target characteristic vectors x '. According to the invention, the problems of meter identification failure and errors caused by accidental shooting factors are greatl</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&amp;date=20200807&amp;DB=EPODOC&amp;CC=CN&amp;NR=111507323A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25543,76294</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20200807&amp;DB=EPODOC&amp;CC=CN&amp;NR=111507323A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>BAI FAN</creatorcontrib><creatorcontrib>HUANG DINGJIANG</creatorcontrib><title>Industrial meter identification method based on multi-frame vision</title><description>The invention discloses an industrial meter identification method based on multi-frame vision. The industrial meter identification method comprises the following steps: 1, continuously shooting N photos towards a preset target near a preset shooting point by utilizing a shooting device; 2, extracting depth features of the N photos through the same set of convolutional neural networks to obtain feature tensors of N HxWxCs, wherein H is the height, W is the width, and C is the length; 3, respectively normalizing the characteristic tensors of the N HxWxCs into an intensity matrix of HxW by utilizing a trained full connection layer; and 4, normalizing each intensity matrix through softmax, and calculating the weighted sum of the characteristic tensors of each characteristic tensor HxWxC through weight to obtain N new vectors with the length of C as target characteristic vectors x '. According to the invention, the problems of meter identification failure and errors caused by accidental shooting factors are greatl</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>eNrjZHDyzEspLS4pykzMUchNLUktUshMSc0ryUzLTE4syczPAwlm5KcoJCUWp6YogPilOSWZumlFibmpCmWZxUAlPAysaYk5xam8UJqbQdHNNcTZQze1ID8-tbggMTk1L7Uk3tnP0NDQ1MDc2MjY0ZgYNQBwUTJV</recordid><startdate>20200807</startdate><enddate>20200807</enddate><creator>BAI FAN</creator><creator>HUANG DINGJIANG</creator><scope>EVB</scope></search><sort><creationdate>20200807</creationdate><title>Industrial meter identification method based on multi-frame vision</title><author>BAI FAN ; HUANG DINGJIANG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN111507323A3</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>BAI FAN</creatorcontrib><creatorcontrib>HUANG DINGJIANG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>BAI FAN</au><au>HUANG DINGJIANG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Industrial meter identification method based on multi-frame vision</title><date>2020-08-07</date><risdate>2020</risdate><abstract>The invention discloses an industrial meter identification method based on multi-frame vision. The industrial meter identification method comprises the following steps: 1, continuously shooting N photos towards a preset target near a preset shooting point by utilizing a shooting device; 2, extracting depth features of the N photos through the same set of convolutional neural networks to obtain feature tensors of N HxWxCs, wherein H is the height, W is the width, and C is the length; 3, respectively normalizing the characteristic tensors of the N HxWxCs into an intensity matrix of HxW by utilizing a trained full connection layer; and 4, normalizing each intensity matrix through softmax, and calculating the weighted sum of the characteristic tensors of each characteristic tensor HxWxC through weight to obtain N new vectors with the length of C as target characteristic vectors x '. According to the invention, the problems of meter identification failure and errors caused by accidental shooting factors are greatl</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language chi ; eng
recordid cdi_epo_espacenet_CN111507323A
source esp@cenet
subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
title Industrial meter identification method based on multi-frame vision
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-22T06%3A33%3A02IST&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=BAI%20FAN&rft.date=2020-08-07&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN111507323A%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