Results

eNauka >  Results >  Towards sustainable societies: Convolutional neural networks optimized by modified crayfish optimization algorithm aided by AdaBoost and XGBoost for waste classification tasks
Title: Towards sustainable societies: Convolutional neural networks optimized by modified crayfish optimization algorithm aided by AdaBoost and XGBoost for waste classification tasks
Authors: A. Tasic; L. Jovanovic ; N. Bacanin  ; M. Zivkovic  ; V. Simic  ; M. Popovic  ; M. Antonijevic  
Issue Date: 2025
Publication: Applied Soft Computing
ISSN: 1568-4946 Applied Soft Computing Search Idenfier
Type: Article
Collation: vol. 175
DOI: 10.1016/j.asoc.2025.113086
WoS-ID: 001469570800001
Scopus-ID: 2-s2.0-105002112557
URI: https://www.sciencedirect.com/science/article/abs/pii/S1568494625003977
https://enauka.gov.rs/handle/123456789/977916
http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/2/11374
URL: https://www.sciencedirect.com/science/article/abs/pii/S1568494625003977?via%3Dihub
Project: Science Fund of the Republic of Serbia [7373, 7502]
Note: PDF je dostupan ali nije otključan
M-category: 
21aM21a

19
SCOPUSTM
16
WEB OF SCIENCETM
Altmetric
Dimensions
Unpaywall

Items in eNauka are protected by copyright, with all rights reserved, unless otherwise indicated.