Moonsoo Jang

Abstract This study presents a data-efficient framework for applying deep learning to forensic shoeprint matching under realistic casework constraints. In forensic practice, deployment is often limited by scarce labeled data, distributional differences between reference collections and casework evidence, and a lack of practical guidance on model selection, augmentation, and adaptation.