47 citations · 63 across the 9 of their papers we have counts for
10 papers
LesionGen: A Concept-Guided Diffusion Model for Dermatology Image Synthesis
Jamil Fayyad, Nourhan Bayasi, Ziyang Yu +1
Deep learning models for skin disease classification require large, diverse, and well-annotated datasets. However, such resources are often limited due to privacy concerns, high an…
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…
Conformal-in-the-Loop for Learning with Imbalanced Noisy Data
John Brandon Graham-Knight, Jamil Fayyad, Nourhan Bayasi +2
Class imbalance and label noise are pervasive in large-scale datasets, yet much of machine learning research assumes well-labeled, balanced data, which rarely reflects real world c…
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…
BiasPruner: Debiased Continual Learning for Medical Image Classification
Nourhan Bayasi, Jamil Fayyad, Alceu Bissoto +2
Continual Learning (CL) is crucial for enabling networks to dynamically adapt as they learn new tasks sequentially, accommodating new data and classes without catastrophic forgetti…
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…
Empirical Validation of Conformal Prediction for Trustworthy Skin Lesions Classification
Jamil Fayyad, Shadi Alijani, Homayoun Najjaran
Background and objective: Uncertainty quantification is a pivotal field that contributes to realizing reliable and robust systems. It becomes instrumental in fortifying safe decisi…
Learning Team-Based Navigation: A Review of Deep Reinforcement Learning Techniques for Multi-Agent Pathfinding
Jaehoon Chung, Jamil Fayyad, Younes Al Younes +1
Multi-agent pathfinding (MAPF) is a critical field in many large-scale robotic applications, often being the fundamental step in multi-agent systems. The increasing complexity of M…
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…