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Found 49 papers, 12 papers with code
Analyzing Covariate Influence on Gender and Race Prediction from Near-Infrared Ocular Images
Recent research has explored the possibility of automatically deducing information such as gender, age and race of an individual from their biometric data.
ATM: A distributed, collaborative, scalable system for automated machine learning
In this paper, we present Auto-Tuned Models, or ATM, a distributed, collaborative, scalable system for automated machine learning.
Semi-Adversarial Networks: Convolutional Autoencoders for Imparting Privacy to Face Images
In this paper, we design and evaluate a convolutional autoencoder that perturbs an input face image to impart privacy to a subject.
Forecasting Pedestrian Trajectory with Machine-Annotated Training Data
In this work, we present a deep learning approach for pedestrian trajectory forecasting using a single vehicle-mounted camera.
D-NetPAD: An Explainable and Interpretable Iris Presentation Attack Detector
An iris recognition system is vulnerable to presentation attacks, or PAs, where an adversary presents artifacts such as printed eyes, plastic eyes, or cosmetic contact lenses to circumvent the system.
DeepTalk: Vocal Style Encoding for Speaker Recognition and Speech Synthesis
Automatic speaker recognition algorithms typically characterize speech audio using short-term spectral features that encode the physiological and anatomical aspects of speech production.
HEFT: Homomorphically Encrypted Fusion of Biometric Templates
This paper proposes a non-interactive end-to-end solution for secure fusion and matching of biometric templates using fully homomorphic encryption (FHE).
Is Style All You Need? Dependencies Between Emotion and GST-based Speaker Recognition
On the task of speech emotion detection, we obtain 80. 8% ACC with acted emotion samples from CREMA-D, 81. 2% ACC with semi-natural emotion samples in IEMOCAP, and 66. 9% ACC with natural emotion samples in MSP-Podcast.
Vocal Style Factorization for Effective Speaker Recognition in Affective Scenarios
The accuracy of automated speaker recognition is negatively impacted by change in emotions in a person's speech.
Investigating Weight-Perturbed Deep Neural Networks With Application in Iris Presentation Attack Detection
In this work, we assess the sensitivity of DNNs against perturbations to their weight and bias parameters.
A Linguistic Comparison between Human and ChatGPT-Generated Conversations
The research also contributes a novel, companion ChatGPT-generated dataset of conversations between two independent chatbots, which were designed to replicate a corpus of human conversations available for open access and used widely in AI research on language modeling.
DeepMasterPrints: Generating MasterPrints for Dictionary Attacks via Latent Variable Evolution
The proposed method, referred to as Latent Variable Evolution, is based on training a Generative Adversarial Network on a set of real fingerprint images.
Biometrics-as-a-Service: A Framework to Promote Innovative Biometric Recognition in the Cloud
This paper presents a framework for Biometrics-as-a-Service (BaaS) that performs biometric matching operations in the cloud, while relying on simple and ubiquitous consumer devices such as smartphones.
Gender Privacy: An Ensemble of Semi Adversarial Networks for Confounding Arbitrary Gender Classifiers
Recent research has proposed the use of Semi Adversarial Networks (SAN) for imparting privacy to face images.
Spoofing PRNU Patterns of Iris Sensors while Preserving Iris Recognition
The principle of Photo Response Non-Uniformity (PRNU) is used to link an image with its source, i. e., the sensor that produced it.
Actions Speak Louder Than (Pass)words: Passive Authentication of Smartphone Users via Deep Temporal Features
Prevailing user authentication schemes on smartphones rely on explicit user interaction, where a user types in a passcode or presents a biometric cue such as face, fingerprint, or iris.
A Comprehensive Overview of Biometric Fusion
A comprehensive review of techniques incorporating ancillary information in the biometric recognition pipeline is also presented.
Matching Thermal to Visible Face Images Using a Semantic-Guided Generative Adversarial Network
Designing face recognition systems that are capable of matching face images obtained in the thermal spectrum with those obtained in the visible spectrum is a challenging problem.
FlowSAN: Privacy-enhancing Semi-Adversarial Networks to Confound Arbitrary Face-based Gender Classifiers
In this regard, Semi-Adversarial Networks (SAN) have recently emerged as a method for imparting soft-biometric privacy to face images.
Some Research Problems in Biometrics: The Future Beckons
The need for reliably determining the identity of a person is critical in a number of different domains ranging from personal smartphones to border security; from autonomous vehicles to e-voting; from tracking child vaccinations to preventing human trafficking; from crime scene investigation to personalization of customer service.
PrivacyNet: Semi-Adversarial Networks for Multi-attribute Face Privacy
Further, PrivacyNet allows a person to choose specific attributes that have to be obfuscated in the input face images (e. g., age and race), while allowing for other types of attributes to be extracted (e. g., gender).
Face Phylogeny Tree Using Basis Functions
We also utilize the same basis functions to model geometric transformations and deep-learning based transformations.
JukeBox: A Multilingual Singer Recognition Dataset
We also evaluate the effect of gender and language on speaker recognition performance, both in spoken and singing voice data.
DeepVOX: Discovering Features from Raw Audio for Speaker Recognition in Non-ideal Audio Signals
The purpose of such a filterbank is to extract features robust to non-ideal audio conditions, such as degraded, short duration, and multi-lingual speech.
Iris Liveness Detection Competition (LivDet-Iris) -- The 2020 Edition
Launched in 2013, LivDet-Iris is an international competition series open to academia and industry with the aim to assess and report advances in iris Presentation Attack Detection (PAD).
Smartphone Camera De-identification while Preserving Biometric Utility
The principle of Photo Response Non Uniformity (PRNU) is often exploited to deduce the identity of the smartphone device whose camera or sensor was used to acquire a certain image.
Attention-Guided Network for Iris Presentation Attack Detection
Two types of attention modules are independently appended on top of the last convolutional layer of the backbone network.
Viability of Optical Coherence Tomography for Iris Presentation Attack Detection
In this paper, we propose the use of Optical Coherence Tomography (OCT) imaging for the problem of iris presentation attack (PA) detection.
Complex-valued Iris Recognition Network
Unlike the problem of general object recognition, where real-valued neural networks can be used to extract pertinent features, iris recognition depends on the extraction of both phase and magnitude information from the input iris texture in order to better represent its biometric content.
CIT-GAN: Cyclic Image Translation Generative Adversarial Network With Application in Iris Presentation Attack Detection
The Styling Network helps the generator to drive the translation of images from a source domain to a reference domain and generate synthetic images with style characteristics of the reference domain.
One-shot Representational Learning for Joint Biometric and Device Authentication
In this work, we propose a method to simultaneously perform (i) biometric recognition (i. e., identify the individual), and (ii) device recognition, (i. e., identify the device) from a single biometric image, say, a face image, using a one-shot schema.
Fingerprint Presentation Attack Detection utilizing Time-Series, Color Fingerprint Captures
This paper demonstrates the viability of utilizing a sensor with time-series and color-sensing capabilities to improve the robustness of a traditional fingerprint sensor and introduces a comprehensive fingerprint dataset with over 36, 000 image sequences and a state-of-the-art set of spoofing techniques.
Conditional Identity Disentanglement for Differential Face Morph Detection
We performed experiments on AMSL face morph, MorGAN, and EMorGAN datasets to demonstrate the effectiveness of the proposed method.
The State of Aerial Surveillance: A Survey
The rapid emergence of airborne platforms and imaging sensors are enabling new forms of aerial surveillance due to their unprecedented advantages in scale, mobility, deployment and covert observation capabilities.
Beyond the Visible: A Survey on Cross-spectral Face Recognition
Secondly, we discuss the appropriate spectral bands for face recognition and discuss recent CFR methods, placing emphasis on deep neural networks.
Trust in AI and Its Role in the Acceptance of AI Technologies
This paper addresses this need by explaining the role of trust on the intention to use AI technologies.
Periocular Biometrics and its Relevance to Partially Masked Faces: A Survey
The performance of face recognition systems can be negatively impacted in the presence of masks and other types of facial coverings that have become prevalent due to the COVID-19 pandemic.
Causality-Inspired Taxonomy for Explainable Artificial Intelligence
As two sides of the same coin, causality and explainable artificial intelligence (xAI) were initially proposed and developed with different goals.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
Can GAN-induced Attribute Manipulations Impact Face Recognition?
Impact due to demographic factors such as age, sex, race, etc., has been studied extensively in automated face recognition systems.
Facial De-morphing: Extracting Component Faces from a Single Morph
In this work, we propose a novel de-morphing method that can recover images of both identities simultaneously from a single morphed face image without needing a reference image or prior information about the morphing process.
Periocular Biometrics: A Modality for Unconstrained Scenarios
Periocular refers to the externally visible region of the face that surrounds the eye socket.
iWarpGAN: Disentangling Identity and Style to Generate Synthetic Iris Images
To overcome these issues, we propose iWarpGAN that disentangles identity and style in the context of the iris modality by using two transformation pathways: Identity Transformation Pathway to generate unique identities from the training set, and Style Transformation Pathway to extract the style code from a reference image and output an iris image using this style.
FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude
Whole-body biometric recognition is an important area of research due to its vast applications in law enforcement, border security, and surveillance.
Synthesizing Forestry Images Conditioned on Plant Phenotype Using a Generative Adversarial Network
Our method helps render the appearance of forest sites specific to a greenness value.
On the Biometric Capacity of Generative Face Models
Our capacity estimates indicate that (a) under ArcFace representation at a false acceptance rate (FAR) of 0. 1%, StyleGAN3 and DCFace have a capacity upper bound of $1. 43\times10^6$ and $1. 190\times10^4$, respectively; (b) the capacity reduces drastically as we lower the desired FAR with an estimate of $1. 796\times10^4$ and $562$ at FAR of 1% and 10%, respectively, for StyleGAN3; (c) there is no discernible disparity in the capacity w. r. t gender; and (d) for some generative models, there is an appreciable disparity in the capacity w. r. t age.
Voice Morphing: Two Identities in One Voice
In a biometric system, each biometric sample or template is typically associated with a single identity.
Iris Presentation Attack: Assessing the Impact of Combining Vanadium Dioxide Films with Artificial Eyes
We observe that the addition of VO2 films on the surface of artificial eyes can cause the PA detection methods to misclassify them as bonafide eyes in some cases.
Iris-SAM: Iris Segmentation Using a Foundational Model
Iris segmentation is a critical component of an iris biometric system and it involves extracting the annular iris region from an ocular image.
Alpha-wolves and Alpha-mammals: Exploring Dictionary Attacks on Iris Recognition Systems
A dictionary attack in a biometric system entails the use of a small number of strategically generated images or templates to successfully match with a large number of identities, thereby compromising security.
