Construction material visual inventory method based on lightweight deep neural network

The invention relates to the technical field of computer vision, in particular to a construction material visual inventory method based on a lightweight deep neural network, and the method comprises the steps: collecting a building material data set, marking a steel bar data set through manual combi...

Full description

Saved in:
Bibliographic Details
Main Authors LIU JIAN, DENG XI, CAO XINYU, LIU SHOUSONG, WANG KAI, YANG YINGMING, QIAN QI
Format Patent
LanguageChinese
English
Published 08.12.2023
Subjects
Online AccessGet full text

Cover

Loading…
Abstract The invention relates to the technical field of computer vision, in particular to a construction material visual inventory method based on a lightweight deep neural network, and the method comprises the steps: collecting a building material data set, marking a steel bar data set through manual combination with semi-automatic marking, and dividing the steel bar data set into a training set and a test set; a lightweight neural network model is designed on the basis of Improved ShufflNet v2; training the lightweight neural network model by using the constructed training set, and preliminarily testing the performance of the lightweight neural network model by using the test set; performing channel pruning on the trained lightweight neural network model based on a BN layer, simplifying the lightweight neural network model, and testing the performance of the pruned lightweight neural network model by using the test set again; and detecting the reinforcing steel bar image by using the trained and pruned lightweight
AbstractList The invention relates to the technical field of computer vision, in particular to a construction material visual inventory method based on a lightweight deep neural network, and the method comprises the steps: collecting a building material data set, marking a steel bar data set through manual combination with semi-automatic marking, and dividing the steel bar data set into a training set and a test set; a lightweight neural network model is designed on the basis of Improved ShufflNet v2; training the lightweight neural network model by using the constructed training set, and preliminarily testing the performance of the lightweight neural network model by using the test set; performing channel pruning on the trained lightweight neural network model based on a BN layer, simplifying the lightweight neural network model, and testing the performance of the pruned lightweight neural network model by using the test set again; and detecting the reinforcing steel bar image by using the trained and pruned lightweight
Author QIAN QI
LIU SHOUSONG
YANG YINGMING
DENG XI
LIU JIAN
WANG KAI
CAO XINYU
Author_xml – fullname: LIU JIAN
– fullname: DENG XI
– fullname: CAO XINYU
– fullname: LIU SHOUSONG
– fullname: WANG KAI
– fullname: YANG YINGMING
– fullname: QIAN QI
BookMark eNqNyz0OgkAQxfEttPDrDuMBLIhGQmmIxsrK2JIVnrIRZsjuAPH2rokHsHn_5vfmZsLCmJlbLhzU96U6YWqtwjvb0OBCH-N4AKv4N7XQWiq624CKomzcs9YR36UK6IjR-_hg6Cj-tTTTh20CVr8uzPp0vObnDTopEDpbIsoivyRJmmTpfpcdtv-YD-MZPF0
ContentType Patent
DBID EVB
DatabaseName esp@cenet
DatabaseTitleList
Database_xml – sequence: 1
  dbid: EVB
  name: esp@cenet
  url: http://worldwide.espacenet.com/singleLineSearch?locale=en_EP
  sourceTypes: Open Access Repository
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
Chemistry
Sciences
Physics
DocumentTitleAlternate 一种基于轻量化深度神经网络的建造物料视觉盘存方法
ExternalDocumentID CN117197649A
GroupedDBID EVB
ID FETCH-epo_espacenet_CN117197649A3
IEDL.DBID EVB
IngestDate Fri Jul 19 13:05:36 EDT 2024
IsOpenAccess true
IsPeerReviewed false
IsScholarly false
Language Chinese
English
LinkModel DirectLink
MergedId FETCHMERGED-epo_espacenet_CN117197649A3
Notes Application Number: CN202310836296
OpenAccessLink https://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20231208&DB=EPODOC&CC=CN&NR=117197649A
ParticipantIDs epo_espacenet_CN117197649A
PublicationCentury 2000
PublicationDate 20231208
PublicationDateYYYYMMDD 2023-12-08
PublicationDate_xml – month: 12
  year: 2023
  text: 20231208
  day: 08
PublicationDecade 2020
PublicationYear 2023
RelatedCompanies CHINA BUILDING TECHNIQUE GROUP CO., LTD
CHONGQING UNIVERSITY
CHINA ACADEMY OF BUILDING RESEARCH
RelatedCompanies_xml – name: CHONGQING UNIVERSITY
– name: CHINA BUILDING TECHNIQUE GROUP CO., LTD
– name: CHINA ACADEMY OF BUILDING RESEARCH
Score 3.6424606
Snippet The invention relates to the technical field of computer vision, in particular to a construction material visual inventory method based on a lightweight deep...
SourceID epo
SourceType Open Access Repository
SubjectTerms CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
Title Construction material visual inventory method based on lightweight deep neural network
URI https://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20231208&DB=EPODOC&locale=&CC=CN&NR=117197649A
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1NT4NAEJ3U-nnTqtH6kTUx3IhFYIEDMXahaUxKG1Ob3pqlSyPGAJFqo7_e2W2xXvREssCGnTC8meXNG4BrKjU_poahc8q5biXc07nwTF02u3JnttkShqxG7kW0-2Q9jO1xDV6qWhilE7pQ4ojoUVP097n6XhfrTaxAcSvLmzjFofyuM_QDbZUdY7By23K1oO2Hg37QZxpjPou06NE3DMdA5LW8-w3YxDDakd4QjtqyKqX4DSmdfdga4GzZ_ABqX88N2GVV57UG7PRWP7wbsK0YmtMSB1deWB7CSHbZrHRfCYac6i0iH2n5jodU0cjzt0-y7A5NJFAJgle-ykR8ofZCiUiSgkgxS7wjW1LBj-CqEw5ZV8dHnfzYZcKi9arMY6hneZacAPGoiB1uJ5x6loUJTcxdm2IciOAs3Jmgp9D8e57mfyfPYE_aWLE53HOo40qTC8TkeXypjPkNdRKSHw
link.rule.ids 230,309,783,888,25576,76876
linkProvider European Patent Office
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1NT8JAEJ0gfuBNUaP4tSamt0Yq7bY9NEa2JahQiKmEG9l2S8SYQixK9Nc7u4B40VOTbbvpTjp9M9s3bwAuqdT8SAxD55Rz3Uy5q3Ph1nTZ7MoZWrWqMGQ1cjukzSfzvm_1C_CyrIVROqEzJY6IHpWgv0_V93qy2sTyFbcyv4pHODS-aUSery2yYwxWrquO5te9oNvxO0xjzGOhFj56hmEbiLyme7sG6xhi29Ibgl5dVqVMfkNKYwc2ujhbNt2FwtdzGUps2XmtDFvtxQ_vMmwqhmaS4-DCC_M96Mkum0vdV4Ihp3qLyMcof8fDSNHIx2-fZN4dmkigEgSvfJWJ-EzthRKRphMixSzxjmxOBd-Hi0YQsaaOjzr4scuAhatV1Q6gmI2z9BCIS0Vscyvl1DVNTGhi7lgU40AEZ-EMBT2Cyt_zVP47eQ6lZtRuDVp34cMxbEt7K2aHcwJFXHV6ivg8jc-UYb8BfBqVEg
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Apatent&rft.title=Construction+material+visual+inventory+method+based+on+lightweight+deep+neural+network&rft.inventor=LIU+JIAN&rft.inventor=DENG+XI&rft.inventor=CAO+XINYU&rft.inventor=LIU+SHOUSONG&rft.inventor=WANG+KAI&rft.inventor=YANG+YINGMING&rft.inventor=QIAN+QI&rft.date=2023-12-08&rft.externalDBID=A&rft.externalDocID=CN117197649A