Deep neural networks have become prevalent in human analysis, boosting the performance
of applications, such as biometric recognition, action recognition, as well as person re …

The state-of-the-art fingerprint matching systems achieve high accuracy on good quality
fingerprints. However, degraded fingerprints obtained due to poor skin conditions of subjects …

A fingerprint region of interest (roi) segmentation algorithm is designed to separate the
foreground fingerprint from the background noise. All the learning based state-of-the-art …

Performance of the state-of-the-art fingerprint denoising model on poor-quality fingerprints
degrades due to cross-domain shift observed between training and testing domains. To …

The state-of-the-art models for fingerprint enhancement are sophisticated deep neural
network architectures that eliminate noise from fingerprints by generating fingerprints image …

Brain cancer ranks among the top ten causes of death globally and stands as the second
leading cause of cancer-related deaths among adolescents. Magnetic Resonance Imaging …

State-of-the-art fingerprint recognition systems perform far from satisfactory on noisy
fingerprints. A fingerprint denoising algorithm is designed to eliminate noise from the input …

Semi-supervised (SS) semantic segmentation exploits both labeled and unlabeled images
to overcome tedious and costly pixel-level annotation problems. Pseudolabel supervision is …

The literature on fingerprint restoration algorithms firmly advocates exploiting contextual
information, such as ridge orientation field, ridge spacing, and ridge frequency, to recover …

Abstract (EN) State-of-the-art machine learning methods such as convolutional neural
networks (CNNs) are frequently employed in computer vision. Despite their high …