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Biometric Identification

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An Improved Multispectral Palmprint Recognition System Using Autoencoder with Regularized Extreme Learning Machine.

Computational intelligence and neuroscience
Multispectral palmprint recognition system (MPRS) is an essential technology for effective human identification and verification tasks. To improve the accuracy and performance of MPRS, a novel approach based on autoencoder (AE) and regularized extrem...

On the Reconstruction of Face Images from Deep Face Templates.

IEEE transactions on pattern analysis and machine intelligence
State-of-the-art face recognition systems are based on deep (convolutional) neural networks. Therefore, it is imperative to determine to what extent face templates derived from deep networks can be inverted to obtain the original face image. In this ...

A critical review on the use of artificial neural networks in olive oil production, characterization and authentication.

Critical reviews in food science and nutrition
Artificial neural networks (ANN) are computationally based mathematical tools inspired by the fundamental cell of the nervous system, the neuron. ANN constitute a simplified artificial replica of the human brain consisting of parallel processing neur...

Analysis of Spatio-Temporal Representations for Robust Footstep Recognition with Deep Residual Neural Networks.

IEEE transactions on pattern analysis and machine intelligence
Human footsteps can provide a unique behavioural pattern for robust biometric systems. We propose spatio-temporal footstep representations from floor-only sensor data in advanced computational models for automatic biometric verification. Our models d...

EAC-Net: Deep Nets with Enhancing and Cropping for Facial Action Unit Detection.

IEEE transactions on pattern analysis and machine intelligence
In this paper, we propose a deep learning based approach for facial action unit (AU) detection by enhancing and cropping regions of interest of face images. The approach is implemented by adding two novel nets (a.k.a. layers): the enhancing layers an...

Feature Extraction with GMDH-Type Neural Networks for EEG-Based Person Identification.

International journal of neural systems
The brain activity observed on EEG electrodes is influenced by volume conduction and functional connectivity of a person performing a task. When the task is a biometric test the EEG signals represent the unique "brain print", which is defined by the ...

Affect recognition from facial movements and body gestures by hierarchical deep spatio-temporal features and fusion strategy.

Neural networks : the official journal of the International Neural Network Society
Affect presentation is periodic and multi-modal, such as through facial movements, body gestures, and so on. Studies have shown that temporal selection and multi-modal combinations may benefit affect recognition. In this article, we therefore propose...

Cross Euclidean-to-Riemannian Metric Learning with Application to Face Recognition from Video.

IEEE transactions on pattern analysis and machine intelligence
Riemannian manifolds have been widely employed for video representations in visual classification tasks including video-based face recognition. The success mainly derives from learning a discriminant Riemannian metric which encodes the non-linear geo...

Sharable and Individual Multi-View Metric Learning.

IEEE transactions on pattern analysis and machine intelligence
This paper presents a sharable and individual multi-view metric learning (MvML) approach for visual recognition. Unlike conventional metric leaning methods which learn a distance metric on either a single type of feature representation or a concatena...

A Grey Wolf Optimizer for Modular Granular Neural Networks for Human Recognition.

Computational intelligence and neuroscience
A grey wolf optimizer for modular neural network (MNN) with a granular approach is proposed. The proposed method performs optimal granulation of data and design of modular neural networks architectures to perform human recognition, and to prove its e...