Sherif Abdulatif — accepted AI-conference papers

2025

Class-Aware PillarMix: Can Mixed Sample Data Augmentation Enhance 3D Object Detection with Radar Point Clouds?

Miao Zhang, Sherif Abdulatif, Benedikt Loesch, Marco Altmann, Bin Yang

IROS 2025

Due to the significant effort required for data collection and annotation in 3D perception tasks, mixed sample data augmentation (MSDA) has been widely studied to generate diverse training samples by mixing existing data. Among these methods, MixUp is a prominent approach that generates new samples

Cited by 1 Source ↗Scholar ↗

2021

Uncertainty-Based Biological Age Estimation of Brain MRI Scans

Karim Armanious, Sherif Abdulatif, Wenbin Shi, Tobias Hepp, Sergios Gatidis, Bin Yang

ICASSP 2021accepted

Age is an essential factor in modern diagnostic procedures. However, assessment of the true biological age (BA) remains a daunting task due to the lack of reference ground-truth labels. Current BA estimation approaches are either restricted to skeletal images or rely on non-imaging modalities that y…

Cited by 0 Source ↗Scholar ↗