activity
20192022
most citedImproving Malaria Parasite Detection from Red Blood Cell using Deep Convolutional Neural Networks

69 citations · 124 across the 7 of their papers we have counts for

collaborators

10 papers

cs.CV202239 cited

Knowledge Distillation approach towards Melanoma Detection

Md. Shakib Khan, Kazi Nabiul Alam, Abdur Rab Dhruba +2

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 tr…

cs.CV20221 cited

VISTA: Vision Transformer enhanced by U-Net and Image Colorfulness Frame Filtration for Automatic Retail Checkout

Md. Istiak Hossain Shihab, Nazia Tasnim, Hasib Zunair +2

Multi-class product counting and recognition identifies product items from images or videos for automated retail checkout. The task is challenging due to the real-world scenario of…

cs.CV2021

STAR: Noisy Semi-Supervised Transfer Learning for Visual Classification

Hasib Zunair, Yan Gobeil, Samuel Mercier +1

Semi-supervised learning (SSL) has proven to be effective at leveraging large-scale unlabeled data to mitigate the dependency on labeled data in order to learn better models for vi…

eess.IV20215 cited

Sharp U-Net: Depthwise Convolutional Network for Biomedical Image Segmentation

Hasib Zunair, A. Ben Hamza

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 se…

eess.IV20213 cited

Synthetic COVID-19 Chest X-ray Dataset for Computer-Aided Diagnosis

Hasib Zunair, A. Ben Hamza

We introduce a new dataset called Synthetic COVID-19 Chest X-ray Dataset for training machine learning models. The dataset consists of 21,295 synthetic COVID-19 chest X-ray images…

cs.CV20212 cited

ViPTT-Net: Video pretraining of spatio-temporal model for tuberculosis type classification from chest CT scans

Hasib Zunair, Aimon Rahman, Nabeel Mohammed

Pretraining has sparked groundswell of interest in deep learning workflows to learn from limited data and improve generalization. While this is common for 2D image classification t…