47 citations · 63 across the 9 of their papers we have counts for
5 papers · 1 filter
Foundation Models as Class-Incremental Learners for Dermatological Image Classification
Mohamed Elkhayat, Mohamed Mahmoud, Jamil Fayyad +1
Class-Incremental Learning (CIL) aims to learn new classes over time without forgetting previously acquired knowledge. The emergence of foundation models (FM) pretrained on large d…
Debiasify: Self-Distillation for Unsupervised Bias Mitigation
Nourhan Bayasi, Jamil Fayyad, Ghassan Hamarneh +2
Simplicity bias poses a significant challenge in neural networks, often leading models to favor simpler solutions and inadvertently learn decision rules influenced by spurious corr…
Sim-to-Real Domain Adaptation for Deformation Classification
Joel Sol, Jamil Fayyad, Shadi Alijani +1
Deformation detection is vital for enabling accurate assessment and prediction of structural changes in materials, ensuring timely and effective interventions to maintain safety an…
Vision transformers in domain adaptation and domain generalization: a study of robustness
Shadi Alijani, Jamil Fayyad, Homayoun Najjaran
Deep learning models are often evaluated in scenarios where the data distribution is different from those used in the training and validation phases. The discrepancy presents a cha…
Model Compression Methods for YOLOv5: A Review
Mohammad Jani, Jamil Fayyad, Younes Al-Younes +1
Over the past few years, extensive research has been devoted to enhancing YOLO object detectors. Since its introduction, eight major versions of YOLO have been introduced with the…