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
Fast Training Methods and Their Experiments for Deep Learni..:
, In:
2021 40th Chinese Control Conference (CCC)
,
Jiang, Shanshan
;
Wang, Sheng-Guo
- p. 8253-8260 , 2021
Link:
https://doi.org/10.23919/CCC52363.2021.9549817
RT T1
2021 40th Chinese Control Conference (CCC)
: T1
Fast Training Methods and Their Experiments for Deep Learning CNN Models
UL https://suche.suub.uni-bremen.de/peid=ieee-9549817&Exemplar=1&LAN=DE A1 Jiang, Shanshan A1 Wang, Sheng-Guo YR 2021 SN 1934-1768 K1 Training K1 Deep learning K1 Costs K1 Neural networks K1 Predictive models K1 Sampling methods K1 Convolutional neural networks K1 Artificial intelligence K1 sampling K1 deep learning K1 fast training K1 convolutional neural network SP 8253 OP 8260 LK http://dx.doi.org/https://doi.org/10.23919/CCC52363.2021.9549817 DO https://doi.org/10.23919/CCC52363.2021.9549817 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)