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
Patch-Level Augmentation for Object Detection in Aerial Ima..:
, In:
2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)
,
Hong, Sungeun
;
Kang, Sungil
;
Cho, Donghyeon
- p. 127-134 , 2019
Link:
https://doi.org/10.1109/ICCVW.2019.00021
RT T1
2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)
: T1
Patch-Level Augmentation for Object Detection in Aerial Images
UL https://suche.suub.uni-bremen.de/peid=ieee-9022567&Exemplar=1&LAN=DE A1 Hong, Sungeun A1 Kang, Sungil A1 Cho, Donghyeon YR 2019 SN 2473-9944 K1 Object detection K1 Training K1 Detectors K1 Proposals K1 Drones K1 Network architecture K1 Shape K1 drone K1 aerial image K1 object detection K1 data augmentation K1 class imbalance SP 127 OP 134 LK http://dx.doi.org/https://doi.org/10.1109/ICCVW.2019.00021 DO https://doi.org/10.1109/ICCVW.2019.00021 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)