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Found 26 papers, 4 papers with code
Is Sharing of Egocentric Video Giving Away Your Biometric Signature?
In this work, we create a novel kind of privacy attack by extracting the wearer’s gait profile, a well known biometric signature, from such optical flow in the egocentric videos.
Impact of Iris Pigmentation on Performance Bias in Visible Iris Verification Systems: A Comparative Study
Furthermore, we examined the generalization capabilities of these systems across different iris colors and devices, finding that while training on diverse datasets enhances recognition performance, the degree of improvement is contingent on the specific model and device used.
TractoEmbed: Modular Multi-level Embedding framework for white matter tract segmentation
White matter tract segmentation is crucial for studying brain structural connectivity and neurosurgical planning.
Tract-RLFormer: A Tract-Specific RL policy based Decoder-only Transformer Network
Fiber tractography is a cornerstone of neuroimaging, enabling the detailed mapping of the brain's white matter pathways through diffusion MRI.
Synthetic Forehead-creases Biometric Generation for Reliable User Verification
In addition, we assess the utility of synthetically generated forehead-crease images using a forehead-crease verification system (FHCVS).
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.
Merry Go Round: Rotate a Frame and Fool a DNN
On the other hand DNNs are known to be susceptible to Adversarial Attacks (AAs) which add im-perceptible noise to the input.
MHATC: Autism Spectrum Disorder identification utilizing multi-head attention encoder along with temporal consolidation modules
Resting-state fMRI is commonly used for diagnosing Autism Spectrum Disorder (ASD) by using network-based functional connectivity.
Anonymizing Egocentric Videos
In a more damaging scenario, one can even recognize a wearer using hand gestures from egocentric videos, or identify a wearer in third person videos such as from a surveillance camera.
IHashNet: Iris Hashing Network based on efficient multi-index hashing
Here, in this paper, we propose an iris indexing scheme using real-valued deep iris features binarized to iris bar codes (IBC) compatible with the indexing structure.
UESegNet: Context Aware Unconstrained ROI Segmentation Networks for Ear Biometric
It has been observed that the proposed models UESegNet-1 and UESegNet-2 outperformed the FRCNN and SSD at higher values of IOUs i. e. an accuracy of 100\% is achieved at IOU 0. 5 on majority of the databases.
Semantic Features Aided Multi-Scale Reconstruction of Inter-Modality Magnetic Resonance Images
Long acquisition time (AQT) due to series acquisition of multi-modality MR images (especially T2 weighted images (T2WI) with longer AQT), though beneficial for disease diagnosis, is practically undesirable.
PoshakNet: Framework for matching dresses from real-life photos using GAN and Siamese Network
We use a Generative Adversarial Network for the task of retrieving the garment that the person in the image was wearing.
VStegNET: Video Steganography Networkusing Spatio-Temporal features andMicro-Bottleneck
Traditional image steganography techniques hide the secret image intohigh-frequency regions of the cover images.
SP-NET: One Shot Fingerprint Singular-Point Detector
Singular points of a fingerprint image are special locations having high curvature properties.
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.
Multiscale CNN based Deep Metric Learning for Bioacoustic Classification: Overcoming Training Data Scarcity Using Dynamic Triplet Loss
Experimental results also confirm the superiority of the triplet loss over the cross-entropy loss in low training data conditions
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.
Learning to Decode 7T-like MR Image Reconstruction from 3T MR Images
Increasing demand for high field magnetic resonance (MR) scanner indicates the need for high-quality MR images for accurate medical diagnosis.
Siamese LSTM based Fiber Structural Similarity Network (FS2Net) for Rotation Invariant Brain Tractography Segmentation
In this paper, we propose a novel deep learning architecture combining stacked Bi-directional LSTM and LSTMs with the Siamese network architecture for segmentation of brain fibers, obtained from tractography data, into anatomically meaningful clusters.
GHCLNet: A Generalized Hierarchically tuned Contact Lens detection Network
The proposed architecture results are quite promising and outperforms the available state-of-the-art lens detection algorithms.
BrainSegNet : A Segmentation Network for Human Brain Fiber Tractography Data into Anatomically Meaningful Clusters
The segregation of brain fiber tractography data into distinct and anatomically meaningful clusters can help to comprehend the complex brain structure and early investigation and management of various neural disorders.
VGR-Net: A View Invariant Gait Recognition Network
It is a 2-stage network, in which we have a classification network that initially identifies the viewing point angle.
UBSegNet: Unified Biometric Region of Interest Segmentation Network
In this paper, we have proposed a novel end-to-end, Unified Biometric ROI Segmentation Network (UBSegNet), for extracting region of interest from five different biometric traits viz.
