بعد أكاديمية كاوست
As of October 2026, Durar is an undergraduate student at King Khalid University. Durar completed the KAUST Academy AI Specialization in September 2026 and placed 4th in the program's image inpainting competition.
المشروع الصيفي
تخصص الذكاء الاصطناعي · دفعة 2026
Explainable Knowledge Distillation for Bone Fracture Classification Using X-ray Images
Bone fracture classification from X-ray images is an important application of deep learning for supporting clinical diagnosis. However, high-capacity models are often computationallyexpensiveanddifficulttointerpret,limitingtheirdeploymentinresource- constrained healthcare environments. This study investigates an Explainable Knowledge Distillation(EKD)frameworkthatcombinesprediction-basedknowledgedistillationwith class-discriminative attention transfer to develop a lightweight and interpretable fracture classifier. Using the FracAtlas dataset, EfficientNet-B6 was selected and optimized as the teacher model, while MobileNetV2 was selected as the lightweight student. The EKD student was evaluatedunder three training settings: No Augmentation, RandAugment, and AugMix, and compared with the corresponding MobileNetV2 baselines. EKD improvedvalidationaccuracyacrossallthreesettings,withAugMixachievingthehighest validationaccuracyof0.8742. Qualitativecomparisonsofteacherandstudentattention maps showed partial spatial correspondence,althoughthe student maps were generally broaderandmorediffuse. Overall,theresultsdemonstratethepotentialofexplainability- guided knowledge distillation for improving lightweight fracture classification while encouraging similarity between teacher andstudent attention patterns.
مع أكاديمية كاوست
- دفعة 2026
جامعة الملك خالد · المدرسة الصيفية للذكاء الاصطناعي
هل تريد تحديث بياناتك أو حذفها؟ تواصل معنا.