1 citations · 2 across the 6 of their papers we have counts for
6 papers
Learning Cross-Joint Attention for Generalizable Video-Based Seizure Detection
Omar Zamzam, Takfarinas Medani, Chinmay Chinara +1
Automated seizure detection from long-term clinical videos can substantially reduce manual review time and enable real-time monitoring. However, existing video-based methods often…
Modeling and Reversing Brain Lesions Using Diffusion Models
Omar Zamzam, Haleh Akrami, Anand Joshi +1
Brain lesions are abnormalities or injuries in brain tissue that are often detectable using magnetic resonance imaging (MRI), which reveals structural changes in the affected areas…
PixelShuffler: A Simple Image Translation Through Pixel Rearrangement
Omar Zamzam
Image-to-image translation is a topic in computer vision that has a vast range of use cases ranging from medical image translation, such as converting MRI scans to CT scans or to o…
Learning A Disentangling Representation For PU Learning
Omar Zamzam, Haleh Akrami, Mahdi Soltanolkotabi +1
In this paper, we address the problem of learning a binary (positive vs. negative) classifier given Positive and Unlabeled data commonly referred to as PU learning. Although rudime…
Beta quantile regression for robust estimation of uncertainty in the presence of outliers
Haleh Akrami, Omar Zamzam, Anand Joshi +2
Quantile Regression (QR) can be used to estimate aleatoric uncertainty in deep neural networks and can generate prediction intervals. Quantifying uncertainty is particularly import…
Learning From Positive and Unlabeled Data Using Observer-GAN
Omar Zamzam, Haleh Akrami, Richard Leahy
The problem of learning from positive and unlabeled data (A.K.A. PU learning) has been studied in a binary (i.e., positive versus negative) classification setting, where the input…