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
A Multi-objective architecture search for generative advers..:
, In:
Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion
,
Kobayashi, Masayuki
;
Nagao, Tomoharu
- p. 133-134 , 2020
Link:
https://dl.acm.org/doi/10.1145/3377929.3390004
RT T1 <cTitle>Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion</cTitle>: T1 <Title>A Multi-objective architecture search for generative adversarial networks</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3390004&Exemplar=1&LAN=DE A1 Kobayashi, Masayuki A1 Nagao, Tomoharu PB ACM YR 2020 K1 deep learning K1 generative adversarial networks K1 image generation K1 multi-objective K1 neural architecture search K1 Computing methodologies K1 Artificial intelligence K1 Search methodologies K1 Heuristic function construction K1 Computer vision K1 Computer vision problems K1 Machine learning K1 Machine learning approaches K1 Neural networks SP 133 OP 134 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3377929.3390004 DO https://dl.acm.org/doi/10.1145/3377929.3390004 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
