57 citations · 108 across the 26 of their papers we have counts for
28 papers
A Dynamically Weighted Loss Function for Unsupervised Image Segmentation
Boujemaa Guermazi, Riadh Ksantini, Naimul Khan
Image segmentation is the foundation of several computer vision tasks, where pixel-wise knowledge is a prerequisite for achieving the desired target. Deep learning has shown promis…
Structure Preserving Cycle-GAN for Unsupervised Medical Image Domain Adaptation
Paolo Iacono, Naimul Khan
The presence of domain shift in medical imaging is a common issue, which can greatly impact the performance of segmentation models when dealing with unseen image domains. Adversari…
Edge-preserving Domain Adaptation for semantic segmentation of Medical Images
Thong Vo, Naimul Khan
Domain Adaptation is a technique to address the lack of massive amounts of labeled data in unseen environments. Unsupervised domain adaptation is proposed to adapt a model to new m…
Interactive segmentation using U-Net with weight map and dynamic user interactions
Ragavie Pirabaharan, Naimul Khan
Interactive segmentation has recently attracted attention for specialized tasks where expert input is required to further enhance the segmentation performance. In this work, we pro…
Online unsupervised Learning for domain shift in COVID-19 CT scan datasets
Nicolas Ewen, Naimul Khan
Neural networks often require large amounts of expert annotated data to train. When changes are made in the process of medical imaging, trained networks may not perform as well, an…
ECG Heart-beat Classification Using Multimodal Image Fusion
Zeeshan Ahmad, Anika Tabassum, Naimul Khan +1
In this paper, we present a novel Image Fusion Model (IFM) for ECG heart-beat classification to overcome the weaknesses of existing machine learning techniques that rely either on…