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
Handwritten Tibetan Digital Words Recognition Based on impr..:
, In:
2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP)
,
Shuai, Qianjun
;
Wu, Xingwen
;
Jin, Libiao
- p. 1-4 , 2019
Link:
https://doi.org/10.1109/ICSIDP47821.2019.9173080
RT T1 <cTitle>2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP)</cTitle>: T1 <Title>Handwritten Tibetan Digital Words Recognition Based on improved Convolutional Neural Network</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9173080&Exemplar=1&LAN=DE A1 Shuai, Qianjun A1 Wu, Xingwen A1 Jin, Libiao YR 2019 K1 Handwritten Tibetan digital words recognition K1 Convolutional Neural Network (CNN) K1 dropout K1 SVM SP 1 OP 4 LK http://dx.doi.org/https://doi.org/10.1109/ICSIDP47821.2019.9173080 DO https://doi.org/10.1109/ICSIDP47821.2019.9173080 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
