I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
House Inspection System Using Artificial Intelligence for C..:
, In:
2023 IEEE 5th Eurasia Conference on IOT, Communication and Engineering (ECICE)
,
Lin, Heng-Xiang
;
Chen, Wei-Jie
;
Lin, Yu-Tong
... - p. 552-556 , 2023
Link:
https://doi.org/10.1109/ECICE59523.2023.10382996
RT T1
2023 IEEE 5th Eurasia Conference on IOT, Communication and Engineering (ECICE)
: T1
House Inspection System Using Artificial Intelligence for Crack Identification
UL https://suche.suub.uni-bremen.de/peid=ieee-10382996&Exemplar=1&LAN=DE A1 Lin, Heng-Xiang A1 Chen, Wei-Jie A1 Lin, Yu-Tong A1 Song, Ye A1 He, Zi-Yi A1 Jian, Lu-Peng A1 Chen, Xin-Yi A1 Wei, Lin A1 Lee, Zne-Jung A1 Chen, Zhong-Yuan YR 2023 K1 Deep learning K1 Industries K1 Technological innovation K1 Learning (artificial intelligence) K1 Inspection K1 Gray-scale K1 Libraries K1 artificial intelligence K1 identify cracks K1 house inspection system K1 CNN convolutional neural network K1 deep learning SP 552 OP 556 LK http://dx.doi.org/https://doi.org/10.1109/ECICE59523.2023.10382996 DO https://doi.org/10.1109/ECICE59523.2023.10382996 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)