Implementation of Vision Transformers for the Matching of Fingerprints in Biometric Verification
Biometric fingerprint recognition is a cornerstone of modern authentication systems, yet conventional convolutional neural network approaches often struggle with challenging cases, subjected to noise and partial overlap. This thesis explores the potential of transformer-based architectures to address these challenges. We design, implement, and evaluate five models on a large-scale dataset of over
