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Found 7 papers, 1 papers with code
LivDet2023 -- Fingerprint Liveness Detection Competition: Advancing Generalization
The International Fingerprint Liveness Detection Competition (LivDet) is a biennial event that invites academic and industry participants to prove their advancements in Fingerprint Presentation Attack Detection (PAD).
Review of the Fingerprint Liveness Detection (LivDet) competition series: from 2009 to 2021
Fingerprint authentication systems are highly vulnerable to artificial reproductions of fingerprint, called fingerprint presentation attacks.
Fingerprint recognition with embedded presentation attacks detection: are we ready?
Accordingly, this paper explores the fusion of PAD into verification systems by proposing a novel investigation instrument: a performance simulator based on the probabilistic modeling of the relationships among the Receiver Operating Characteristics (ROC) of the two individual systems when PAD and verification stages are implemented sequentially.
LivDet 2021 Fingerprint Liveness Detection Competition -- Into the unknown
The International Fingerprint Liveness Detection Competition is an international biennial competition open to academia and industry with the aim to assess and report advances in Fingerprint Presentation Attack Detection.
Electroencephalography signal processing based on textural features for monitoring the driver's state by a Brain-Computer Interface
The claim is that the class transitions can be detected by describing the variations of the micro-patterns' occurrences along the EEG signal.
Are Adaptive Face Recognition Systems still Necessary? Experiments on the APE Dataset
In the last five years, deep learning methods, in particular CNN, have attracted considerable attention in the field of face-based recognition, achieving impressive results.
LivDet in Action - Fingerprint Liveness Detection Competition 2019
The International Fingerprint liveness Detection Competition (LivDet) is an open and well-acknowledged meeting point of academies and private companies that deal with the problem of distinguishing images coming from reproductions of fingerprints made of artificial materials and images relative to real fingerprints.
