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
Psyncgan for Data Generation Application of Partially Syncr..:
, In:
Proceedings of the 2019 3rd International Conference on Advances in Image Processing
,
Valery, Kovtun
;
Siahroudi, Sajjad Kamali
;
Gang, Wei
- p. 92-96 , 2019
Link:
https://dl.acm.org/doi/10.1145/3373419.3373431
RT T1 <cTitle>Proceedings of the 2019 3rd International Conference on Advances in Image Processing</cTitle>: T1 <Title>Psyncgan for Data Generation Application of Partially Syncronized GAN to Image and Caption Data Generation</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3373431&Exemplar=1&LAN=DE A1 Valery, Kovtun A1 Siahroudi, Sajjad Kamali A1 Gang, Wei PB ACM YR 2019 K1 Asymmetric Distributions K1 Attention based mechanisms K1 Big Data K1 Data Generation K1 Deep Generative Methods K1 Dual-Learning K1 GAN K1 Image Captioning K1 Image Generation K1 Limited Datasets K1 Machine Learning K1 Semi-Supervised Learning K1 Computing methodologies K1 Machine learning K1 Learning settings K1 Semi-supervised learning settings SP 92 OP 96 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3373419.3373431 DO https://dl.acm.org/doi/10.1145/3373419.3373431 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
