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CosSIF: Cosine similarity-based image filtering to overcome low inter-class variation in synthetic medical image datasets

Author(s): Islam M; Zunair H; Mohammed N;

Crafting effective deep learning models for medical image analysis is a complex task, particularly in cases where the medical image dataset lacks significant inter-class variation. This challenge is further aggravated when employing such datasets to generat ...

Article GUID: 38492455


Quantifying imbalanced classification methods for leukemia detection

Author(s): Depto DS; Rizvee MM; Rahman A; Zunair H; Rahman MS; Mahdy MRC;

Uncontrolled proliferation of B-lymphoblast cells is a common characterization of Acute Lymphoblastic Leukemia (ALL). B-lymphoblasts are found in large numbers in peripheral blood in malignant cases. Early detection of the cell in bone marrow is essential a ...

Article GUID: 36516574


Knowledge distillation approach towards melanoma detection

Author(s): Khan MS; Alam KN; Dhruba AR; Zunair H; Mohammed N;

Melanoma is regarded as the most threatening among all skin cancers. There is a pressing need to build systems which can aid in the early detection of melanoma and enable timely treatment to patients. Recent methods are geared towards machine learning based ...

Article GUID: 35594685


Sharp U-Net: Depthwise convolutional network for biomedical image segmentation

Author(s): Zunair H; Ben Hamza A;

The U-Net architecture, built upon the fully convolutional network, has proven to be effective in biomedical image segmentation. However, U-Net applies skip connections to merge semantically different low- and high-level convolutional features, resulting in ...

Article GUID: 34348214


A comparative analysis of deep learning architectures on high variation malaria parasite classification dataset.

Author(s): Rahman A, Zunair H, Reme TR, Rahman MS, Mahdy MRC

Malaria, one of the leading causes of death in underdeveloped countries, is primarily diagnosed using microscopy. Computer-aided diagnosis of malaria is a challenging task owing to the fine-grained variability in the appearance of some uninfected and infect ...

Article GUID: 33465520


Melanoma detection using adversarial training and deep transfer learning.

Author(s): Zunair H, Ben Hamza A

Phys Med Biol. 2020 Apr 06;: Authors: Zunair H, Ben Hamza A

Article GUID: 32252036


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