@article{0403764339fd46749d6c8ac2b7f423e6,
title = "AHA-AO: Artificial Hummingbird Algorithm with Aquila Optimization for Efficient Feature Selection in Medical Image Classification",
keywords = "Aquila Optimization, Artificial Hummingbird Algorithm, feature selection algorithms, medical image classification, MobileNet",
author = "Elaziz, {Mohamed Abd} and Abdelghani Dahou and Shaker El-Sappagh and Alhassan Mabrouk and Gaber, {Mohamed Medhat}",
note = "Funding Information: This work has received financial support from the European Regional Development Fund (tRDF) and the Galician Regional Government, under the agreement for funding the Atlantic Research Center for Information and Communication Technologies (atlanTTic). This work was also supported by the Spanish Government under re-search project “Enhancing Communication Protocols with Machine Learning while Protecting Sensitive Data (COMPROMISE)” (PID2020-113795RB-C33/AEI/10.13039/501100011033). Publisher Copyright: {\textcopyright} 2022 by the authors.",
year = "2022",
month = oct,
doi = "10.3390/app12199710",
language = "English",
volume = "12",
journal = "Applied Sciences (Switzerland)",
issn = "2076-3417",
publisher = "MDPI",
number = "19",
}