104 citations · 254 across the 13 of their papers we have counts for
8 papers · 1 filter
RSUD20K: A Dataset for Road Scene Understanding In Autonomous Driving
Hasib Zunair, Shakib Khan, A. Ben Hamza
Road scene understanding is crucial in autonomous driving, enabling machines to perceive the visual environment. However, recent object detectors tailored for learning on datasets…
Learning to recognize occluded and small objects with partial inputs
Hasib Zunair, A. Ben Hamza
Recognizing multiple objects in an image is challenging due to occlusions, and becomes even more so when the objects are small. While promising, existing multi-label image recognit…
CosSIF: Cosine similarity-based image filtering to overcome low inter-class variation in synthetic medical image datasets
Mominul Islam, Hasib Zunair, Nabeel Mohammed
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.…
Masked Supervised Learning for Semantic Segmentation
Hasib Zunair, A. Ben Hamza
Self-attention is of vital importance in semantic segmentation as it enables modeling of long-range context, which translates into improved performance. We argue that it is equally…
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…
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…
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…
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…