A hybrid FL-enabled ensemble approach for lung disease diagnosis leveraging fusion of SWIN transformer and CNN

A hybrid FL-enabled ensemble approach for lung disease diagnosis leveraging fusion of SWIN transformer and CNN

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This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.

Détails bibliographiques
Auteurs principaux:	Chowdhury, Asif Hasan, Islam, Md. Fahim, Riad, M Ragib Anjum, Hashem, Faiyaz Bin
Autres auteurs:	Alam, Md. Golam Rabiul
Format:	Thèse
Langue:	English
Publié:	Brac University 2023
Sujets:	AI VGG19 Inception V3 DenseNet201 SWIN transformer Feder- ated learning Biomedical engineering Neural networks (Computer science)
Accès en ligne:	http://hdl.handle.net/10361/21844

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