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
Classification and Identifying Human Body Skin Lesions usin..:
, In:
2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS)
,
Deepasundari, K.
;
Raja, A. Thirumurthi
- p. 1511-1518 , 2023
Link:
https://doi.org/10.1109/ICACRS58579.2023.10405228
RT T1 <cTitle>2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS)</cTitle>: T1 <Title>Classification and Identifying Human Body Skin Lesions using Proposed RCDNN</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10405228&Exemplar=1&LAN=DE A1 Deepasundari, K. A1 Raja, A. Thirumurthi YR 2023 K1 Image processing K1 Computational modeling K1 Skin K1 Mathematical models K1 Lesions K1 Time factors K1 Diseases K1 Skin Lesions K1 Machine Learning K1 Deep Learning K1 Artificial Neural Network K1 Convolutional Neural Network K1 Recurrence Neural Network K1 Deep Neural Network and Regional Convolutional Dense Neural Network SP 1511 OP 1518 LK http://dx.doi.org/https://doi.org/10.1109/ICACRS58579.2023.10405228 DO https://doi.org/10.1109/ICACRS58579.2023.10405228 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
