AIMC Topic: Biometric Identification

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Person identification from EEG using various machine learning techniques with inter-hemispheric amplitude ratio.

PloS one
Association between electroencephalography (EEG) and individually personal information is being explored by the scientific community. Though person identification using EEG is an attraction among researchers, the complexity of sensing limits using su...

Detecting face presentation attacks in mobile devices with a patch-based CNN and a sensor-aware loss function.

PloS one
With the widespread use of biometric authentication comes the exploitation of presentation attacks, possibly undermining the effectiveness of these technologies in real-world setups. One example takes place when an impostor, aiming at unlocking someo...

Deep Learning-Based Real-Time Multiple-Person Action Recognition System.

Sensors (Basel, Switzerland)
Action recognition has gained great attention in automatic video analysis, greatly reducing the cost of human resources for smart surveillance. Most methods, however, focus on the detection of only one action event for a single person in a well-segme...

DE-CNN: An Improved Identity Recognition Algorithm Based on the Emotional Electroencephalography.

Computational and mathematical methods in medicine
In the past few decades, identification recognition based on electroencephalography (EEG) has received extensive attention to resolve the security problems of conventional biometric systems. In the present study, a novel EEG-based identification syst...

Can Ensemble Deep Learning Identify People by Their Gait Using Data Collected from Multi-Modal Sensors in Their Insole?

Sensors (Basel, Switzerland)
Gait is a characteristic that has been utilized for identifying individuals. As human gait information is now able to be captured by several types of devices, many studies have proposed biometric identification methods using gait information. As rese...

Feature fusion via Deep Random Forest for facial age estimation.

Neural networks : the official journal of the International Neural Network Society
In the last few years, human age estimation from face images attracted the attention of many researchers in computer vision and machine learning fields. This is due to its numerous applications. In this paper, we propose a new architecture for age es...

Opportunities and challenges of deep learning methods for electrocardiogram data: A systematic review.

Computers in biology and medicine
BACKGROUND: The electrocardiogram (ECG) is one of the most commonly used diagnostic tools in medicine and healthcare. Deep learning methods have achieved promising results on predictive healthcare tasks using ECG signals.

An end-to-end exemplar association for unsupervised person Re-identification.

Neural networks : the official journal of the International Neural Network Society
Tracklet association methods learn the cross camera retrieval ability though associating underlying cross camera positive samples, which have proven to be successful in unsupervised person re-identification task. However, most of them use poor-effici...

Cross-modality paired-images generation and augmentation for RGB-infrared person re-identification.

Neural networks : the official journal of the International Neural Network Society
RGB-Infrared (IR) person re-identification is very challenging due to the large cross-modality variations between RGB and IR images. Considering no correspondence labels between every pair of RGB and IR images, most methods try to alleviate the varia...

End-to-End Deep Learning Fusion of Fingerprint and Electrocardiogram Signals for Presentation Attack Detection.

Sensors (Basel, Switzerland)
Although fingerprint-based systems are the commonly used biometric systems, they suffer from a critical vulnerability to a presentation attack (PA). Therefore, several approaches based on a fingerprint biometrics have been developed to increase the r...