An interpretable transformer based approach to classify Malaria from blood cell images
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.
Egile Nagusiak: | Islam, Mehafuza, Al Mamun, S.M. Abdulla |
---|---|
Beste egile batzuk: | Alam, Dr. Md. Ashraful |
Formatua: | Thesis |
Hizkuntza: | English |
Argitaratua: |
Brac University
2023
|
Gaiak: | |
Sarrera elektronikoa: | http://hdl.handle.net/10361/20000 |
Antzeko izenburuak
-
An interpretable diagnosis of retinal diseases using vision transformer and Grad-CAM
nork: Bhuiyan, Mahdi Hasan, et al.
Argitaratua: (2024) -
Deep learning-based waste classification system for efficient waste management
nork: Nakib, Abdullah Al, et al.
Argitaratua: (2022) -
Deep Learning based Medicinal Plants Leaf Recognition
nork: Mahalanabish, Tonusri
Argitaratua: (2023) -
Analysis of transformer and CNN based approaches for classifying renal abnormality from image data
nork: Reza, S. M. Mushfiq, et al.
Argitaratua: (2024) -
Performance comparison of CNN architectures for detecting Malaria diseases
nork: Rinky, Habiba Karim, et al.
Argitaratua: (2021)