Deep learning for biometrics: A survey
K Sundararajan, DL Woodard - ACM Computing Surveys (CSUR), 2018 - dl.acm.org
In the recent past, deep learning methods have demonstrated remarkable success for
supervised learning tasks in multiple domains including computer vision, natural language …
supervised learning tasks in multiple domains including computer vision, natural language …
Automated latent fingerprint identification system: A review
Latent fingerprints are considered as one of the important evidences obtained from the site
of crime. The process of developing, acquiring, processing and matching of latent …
of crime. The process of developing, acquiring, processing and matching of latent …
DeFFusion: CNN-based continuous authentication using deep feature fusion
Smartphones have become crucial and important in our daily life, but the security and
privacy issues have been major concerns of smartphone users. In this article, we present …
privacy issues have been major concerns of smartphone users. In this article, we present …
Invisible poison: A blackbox clean label backdoor attack to deep neural networks
This paper reports a new clean-label data poisoning backdoor attack, named Invisible
Poison, which stealthily and aggressively plants a backdoor in neural networks. It converts a …
Poison, which stealthily and aggressively plants a backdoor in neural networks. It converts a …
Radio frequency fingerprint-based drone identification and classification using Mel spectrograms and pre-trained YAMNet neural
The convergence of drones with the Internet of Things (IoT) has paved the way for the
Internet of Drones (IoD), an interconnected network of drones, ground control systems, and …
Internet of Drones (IoD), an interconnected network of drones, ground control systems, and …
Recreating fingerprint images by convolutional neural network autoencoder architecture
Fingerprint recognition systems have been applied widely to adopt accurate and reliable
biometric identification between individuals. Deep learning, especially Convolutional Neural …
biometric identification between individuals. Deep learning, especially Convolutional Neural …
Fingerprint classification using a deep convolutional neural network
Biometric systems detect authenticity based on users' distinct physiological or behavioral
characteristics for purposes of identification and access control. These pattern recognition …
characteristics for purposes of identification and access control. These pattern recognition …
[HTML][HTML] Person identification from fingernails and knuckles images using deep learning features and the Bray-Curtis similarity measure
In this paper, an approach that makes use of knuckle creases and fingernails for person
identification is presented. It introduces a framework for automatic person identification that …
identification is presented. It introduces a framework for automatic person identification that …
Deep learning algorithms based fingerprint authentication: systematic literature review
H Chiroma - Journal of Artificial Intelligence and Systems, 2021 - iecscience.org
Deep Learning algorithms (DL) have been applied in different domains such as computer
vision, image detection, robotics and speech processing, in most cases, DL demonstrated …
vision, image detection, robotics and speech processing, in most cases, DL demonstrated …
Query2set: Single-to-multiple partial fingerprint recognition based on attention mechanism
Currently, fingerprint authentication systems in mobile devices, which have limited-size
fingerprint sensors, are mainly based on partial fingerprint matching algorithms. To cover all …
fingerprint sensors, are mainly based on partial fingerprint matching algorithms. To cover all …