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Found 23 papers, 7 papers with code
Fingerprint Template Invertibility: Minutiae vs. Deep Templates
We show that while a deep template can be inverted to produce a fingerprint image that could be matched to its source image, deep templates are more resistant to reconstruction attacks than minutiae templates.
3D Graph Anatomy Geometry-Integrated Network for Pancreatic Mass Segmentation, Diagnosis, and Quantitative Patient Management
We exploit the feasibility to distinguish pancreatic ductal adenocarcinoma (PDAC) from the nine other nonPDAC masses using multi-phase CT imaging.
Infant-ID: Fingerprints for Global Good
In many of the least developed and developing countries, a multitude of infants continue to suffer and die from vaccine-preventable diseases and malnutrition.
Robust Pancreatic Ductal Adenocarcinoma Segmentation with Multi-Institutional Multi-Phase Partially-Annotated CT Scans
A student model is trained on both manual and pseudo annotated multi-phase images.
Learning a Fixed-Length Fingerprint Representation
DeepPrint incorporates fingerprint domain knowledge, including alignment and minutiae detection, into the deep network architecture to maximize the discriminative power of its representation.
Fingerprints: Fixed Length Representation via Deep Networks and Domain Knowledge
We learn a discriminative fixed length feature representation of fingerprints which stands in contrast to commonly used unordered, variable length sets of minutiae points.
Latent Fingerprint Recognition: Role of Texture Template
We propose a texture template approach, consisting of a set of virtual minutiae, to improve the overall latent fingerprint recognition accuracy.
Automatic Latent Fingerprint Segmentation
We present a simple but effective method for automatic latent fingerprint segmentation, called SegFinNet.
Fingerprint Match in Box
We open source fingerprint Match in Box, a complete end-to-end fingerprint recognition system embedded within a 4 inch cube.
Matching Fingerphotos to Slap Fingerprint Images
We address the problem of comparing fingerphotos, fingerprint images from a commodity smartphone camera, with the corresponding legacy slap contact-based fingerprint images.
RaspiReader: Open Source Fingerprint Reader
Finally, fingerprint matching experiments between images acquired from the FTIR output of RaspiReader and images acquired from a COTS reader verify the interoperability of the RaspiReader with existing COTS optical readers.
Robust Minutiae Extractor: Integrating Deep Networks and Fingerprint Domain Knowledge
Further, our method finds minutiae sets that are better in terms of precision and recall in comparison with state-of-the-art on these two datasets.
Fingerprint Spoof Buster
Experimental results on three public-domain LivDet datasets (2011, 2013, and 2015) show that the proposed approach provides state-of-the-art accuracies in fingerprint spoof detection for intra-sensor, cross-material, cross-sensor, as well as cross-dataset testing scenarios.
RaspiReader: An Open Source Fingerprint Reader Facilitating Spoof Detection
Finally, fingerprint matching experiments between images acquired from the FTIR output of the RaspiReader and images acquired from a COTS fingerprint reader verify the interoperability of the RaspiReader with existing COTS optical readers.
Automated Latent Fingerprint Recognition
Experimental results show that the rank-1 identification accuracies (query latent is matched with its true mate in the reference database) are 64. 7% for the NIST SD27 and 75. 3% for the WVU latent databases, against a reference database of 100K rolled prints.
On the Reconstruction of Face Images from Deep Face Templates
Our study demonstrates the need to secure deep templates in face recognition systems.
Biometrics for Child Vaccination and Welfare: Persistence of Fingerprint Recognition for Infants and Toddlers
However, persistence of biometric recognition accuracy has not been studied systematically for children in the age group of 0-4 years.
Jointly Embedding Relations and Mentions for Knowledge Population
This paper contributes a joint embedding model for predicting relations between a pair of entities in the scenario of relation inference.
