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Found 8 papers, 1 papers with code
FH-SSTNet: Forehead Creases based User Verification using Spatio-Spatial Temporal Network
The results demonstrate the superior performance of FH-SSTNet for forehead-based user verification, confirming its effectiveness in identity authentication.
Vulnerability of Face Morphing Attacks: A Case Study on Lookalike and Identical Twins
We present a systematic study on benchmarking the vulnerability of Face Recognition Systems (FRS) to lookalike and identical twin morphing images.
Towards the Generation of Synthetic Images of Palm Vein Patterns: A Review
With the recent success of computer vision and deep learning, remarkable progress has been achieved on automatic personal recognition using vein biometrics.
DFCANet: Dense Feature Calibration-Attention Guided Network for Cross Domain Iris Presentation Attack Detection
To alleviate these shortcomings, this paper proposes DFCANet: Dense Feature Calibration and Attention Guided Network which calibrates the locally spread iris patterns with the globally located ones.
Cross-Domain Iris Presentation Attack Detection
Incremental Learning
+1
FKIMNet: A Finger Dorsal Image Matching Network Comparing Component (Major, Minor and Nail) Matching with Holistic (Finger Dorsal) Matching
In distinguished experiments, the individual performance of finger, as well as weighted sum score level fusion of major knuckle, minor knuckle, and nail modalities have been computed, justifying our assumption to consider full finger as biometrics instead of its counterparts.
FDSNet: Finger dorsal image spoof detection network using light field camera
At present spoofing attacks via which biometric system is potentially vulnerable against a fake biometric characteristic, introduces a great challenge to recognition performance.
PVSNet: Palm Vein Authentication Siamese Network Trained using Triplet Loss and Adaptive Hard Mining by Learning Enforced Domain Specific Features
Designing an end-to-end deep learning network to match the biometric features with limited training samples is an extremely challenging task.
FDFNet : A Secure Cancelable Deep Finger Dorsal Template Generation Network Secured via. Bio-Hashing
In this work, we have proposed a secure cancelable finger dorsal template generation network (learning domain specific features) secured via.
