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
NFFKD: A Knowledge Distillation Method Based on Normalized ..:
, In:
2022 IEEE 5th International Conference on Big Data and Artificial Intelligence (BDAI)
,
Wang, Zihan
;
Xie, Junwei
;
Yao, Zhiping
... - p. 111-116 , 2022
Link:
https://doi.org/10.1109/BDAI56143.2022.9862657
RT T1
2022 IEEE 5th International Conference on Big Data and Artificial Intelligence (BDAI)
: T1
NFFKD: A Knowledge Distillation Method Based on Normalized Feature Fusion Model
UL https://suche.suub.uni-bremen.de/peid=ieee-9862657&Exemplar=1&LAN=DE A1 Wang, Zihan A1 Xie, Junwei A1 Yao, Zhiping A1 Kuang, Xu A1 Gao, Qinquan A1 Tong, Tong YR 2022 K1 Knowledge engineering K1 Big Data K1 Benchmark testing K1 Robustness K1 knowledge distillation K1 deep learning K1 convolutional neural network K1 knowledge transfer SP 111 OP 116 LK http://dx.doi.org/https://doi.org/10.1109/BDAI56143.2022.9862657 DO https://doi.org/10.1109/BDAI56143.2022.9862657 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)