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
Machine Learning Model for Multiclass Lesion Diagnoses:
, In:
2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)
,
Ismail, Karim E.
;
AbouRizka, Mohamed A.
;
Maghraby, Fahima A.
- p. 397-402 , 2020
Link:
https://doi.org/10.1109/NILES50944.2020.9257976
RT T1
2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)
: T1
Machine Learning Model for Multiclass Lesion Diagnoses
UL https://suche.suub.uni-bremen.de/peid=ieee-9257976&Exemplar=1&LAN=DE A1 Ismail, Karim E. A1 AbouRizka, Mohamed A. A1 Maghraby, Fahima A. YR 2020 K1 Lesions K1 Image color analysis K1 Melanoma K1 Support vector machines K1 Feature extraction K1 Machine learning K1 Computational modeling K1 Dermoscopic image K1 HOG K1 Lesion K1 morphological operations K1 PCA K1 random forest K1 SIFT K1 SVM SP 397 OP 402 LK http://dx.doi.org/https://doi.org/10.1109/NILES50944.2020.9257976 DO https://doi.org/10.1109/NILES50944.2020.9257976 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)