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
A Novel Approach for Detecting the Malignant Features of Br..:
, In:
2022 IEEE International Conference on Data Science and Information System (ICDSIS)
,
Aggarwal, Ritu
;
Thakral, Prateek
- p. 1-4 , 2022
Link:
https://doi.org/10.1109/ICDSIS55133.2022.9915954
RT T1 <cTitle>2022 IEEE International Conference on Data Science and Information System (ICDSIS)</cTitle>: T1 <Title>A Novel Approach for Detecting the Malignant Features of Breast Cancer using Algorithms of ML</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9915954&Exemplar=1&LAN=DE A1 Aggarwal, Ritu A1 Thakral, Prateek YR 2022 K1 Support vector machines K1 Radio frequency K1 Measurement K1 Machine learning algorithms K1 Image edge detection K1 Feature extraction K1 Breast cancer K1 Machine Learning K1 BC K1 Malignant K1 Benign K1 FNA K1 SVM K1 KNN K1 NB K1 Decision Tree SP 1 OP 4 LK http://dx.doi.org/https://doi.org/10.1109/ICDSIS55133.2022.9915954 DO https://doi.org/10.1109/ICDSIS55133.2022.9915954 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
