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.

Detalles Bibliográficos
Main Authors: Chowdhury, Asif Hasan, Islam, Md. Fahim, Riad, M Ragib Anjum, Hashem, Faiyaz Bin
Outros autores: Alam, Md. Golam Rabiul
Formato: Thesis
Idioma:English
Publicado: Brac University 2023
Subjects:
AI
VGG19
Inception V3
DenseNet201
SWIN transformer
Feder- ated learning
Biomedical engineering
Neural networks (Computer science)
Acceso en liña:http://hdl.handle.net/10361/21844

Internet

http://hdl.handle.net/10361/21844

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