Ammar Ahmed
Publikasjoner
Enhancing wrist abnormality detection with yolo: Analysis of state-of-the-art single-stage detection models
This study employs single-stage deep neural network-based detection models. Our models outperform the commonly used two-stage detection algorithm, Faster R-CNN, in fracture detection, enhancing pediatric wrist imaging.
Learning from the few: Fine-grained approach to pediatric wrist pathology recognition on a limited dataset
Wrist pathology recognition reframed as fine-grained problem; outperforms existing techniques. LION optimizer integration enhances network’s performance. XAI integrated into architecture for pinpointing discriminative regions in wrist X-rays.