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
Effective Insect Recognition Based on Deep Neural Network M..:
, In:
2021 5th International Conference on High Performance Compilation, Computing and Communications
,
Yang, Fan
;
Li, Feifei
;
Xu, Jie
... - p. 62-67 , 2021
Link:
https://dl.acm.org/doi/10.1145/3471274.3471285
RT T1 <cTitle>2021 5th International Conference on High Performance Compilation, Computing and Communications</cTitle>: T1 <Title>Effective Insect Recognition Based on Deep Neural Network Models in Complex Background</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3471285&Exemplar=1&LAN=DE A1 Yang, Fan A1 Li, Feifei A1 Xu, Jie A1 Su, Guanghui A1 Li, Jianhui A1 Ji, Meng A1 Xiong, Wenjie A1 Zhao, Bo PB ACM YR 2021 K1 Inception V3 K1 ResNet50 K1 VGG16_bn K1 deep learning K1 insect recognition K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Neural networks SP 62 OP 67 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3471274.3471285 DO https://dl.acm.org/doi/10.1145/3471274.3471285 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
