A hybrid FL-Enabled ensemble approach for lung disease diagnosis leveraging fusion of SWIN transformer and CNN
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
Κύριοι συγγραφείς: | Chowdhury, Asif Hasan, Islam, Md. Fahim, Riad, M Ragib Anjum, Hashem, Faiyaz Bin |
---|---|
Άλλοι συγγραφείς: | Alam, Md. Golam Rabiul |
Μορφή: | Thesis |
Γλώσσα: | English |
Έκδοση: |
Brac University
2023
|
Θέματα: | |
Διαθέσιμο Online: | http://hdl.handle.net/10361/21851 |
Παρόμοια τεκμήρια
-
A hybrid FL-enabled ensemble approach for lung disease diagnosis leveraging fusion of SWIN transformer and CNN
ανά: Chowdhury, Asif Hasan, κ.ά.
Έκδοση: (2023) -
Detection of coronary artery blockage at an early stage using effective deep learning technique
ανά: Promit, Tahmid Ashrafee, κ.ά.
Έκδοση: (2023) -
Prediction of glaucoma from fundus images leveraging transfer learning in deep neural network
ανά: Ismail, Sayem Mohammad, κ.ά.
Έκδοση: (2021) -
MalFam: a comprehensive study on malware families with state-of-the-art CNN architectures with classifications and XAI
ανά: Haque, Abid Hossain, κ.ά.
Έκδοση: (2024) -
Cassava leaf disease classification using deep learning and convolutional neural network ensemble
ανά: Shahriar, Hasan, κ.ά.
Έκδοση: (2022)