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
Combining Convolutional Neural Networks and Random Forest f..:
, In:
2024 International Conference on Automation and Computation (AUTOCOM)
,
Chakram, Prince Kumar
;
Kumar, Vishal
;
Khan, Aquib
. - p. 20-23 , 2024
Link:
https://doi.org/10.1109/AUTOCOM60220.2024.10486155
RT T1 <cTitle>2024 International Conference on Automation and Computation (AUTOCOM)</cTitle>: T1 <Title>Combining Convolutional Neural Networks and Random Forest for Lotus Multi-Classification</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10486155&Exemplar=1&LAN=DE A1 Chakram, Prince Kumar A1 Kumar, Vishal A1 Khan, Aquib A1 Kukreja, Vinay YR 2024 K1 Earth K1 Deep learning K1 Costs K1 Computational modeling K1 Organizations K1 Data augmentation K1 Data models K1 classification of lotus K1 convolutional neural network K1 random-forest K1 max-pooling SP 20 OP 23 LK http://dx.doi.org/https://doi.org/10.1109/AUTOCOM60220.2024.10486155 DO https://doi.org/10.1109/AUTOCOM60220.2024.10486155 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
