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Biometry

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HTM Spatial Pooler With Memristor Crossbar Circuits for Sparse Biometric Recognition.

IEEE transactions on biomedical circuits and systems
Hierarchical Temporal Memory (HTM) is an online machine learning algorithm that emulates the neo-cortex. The development of a scalable on-chip HTM architecture is an open research area. The two core substructures of HTM are spatial pooler and tempora...

Classification and Verification of Handwritten Signatures with Time Causal Information Theory Quantifiers.

PloS one
We present a new approach for handwritten signature classification and verification based on descriptors stemming from time causal information theory. The proposal uses the Shannon entropy, the statistical complexity, and the Fisher information evalu...

Flexible variable selection for recovering sparsity in nonadditive nonparametric models.

Biometrics
Variable selection for recovering sparsity in nonadditive and nonparametric models with high-dimensional variables has been challenging. This problem becomes even more difficult due to complications in modeling unknown interaction terms among high-di...

Calibrating random forests for probability estimation.

Statistics in medicine
Probabilities can be consistently estimated using random forests. It is, however, unclear how random forests should be updated to make predictions for other centers or at different time points. In this work, we present two approaches for updating ran...

Body-Based Gender Recognition Using Images from Visible and Thermal Cameras.

Sensors (Basel, Switzerland)
Gender information has many useful applications in computer vision systems, such as surveillance systems, counting the number of males and females in a shopping mall, accessing control systems in restricted areas, or any human-computer interaction sy...

Multiple kernel learning with random effects for predicting longitudinal outcomes and data integration.

Biometrics
Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although, kernel-based st...

Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines.

Sensors (Basel, Switzerland)
Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vec...

Asymptotic accuracy of Bayesian estimation for a single latent variable.

Neural networks : the official journal of the International Neural Network Society
In data science and machine learning, hierarchical parametric models, such as mixture models, are often used. They contain two kinds of variables: observable variables, which represent the parts of the data that can be directly measured, and latent v...

A support vector machine approach for truncated fingerprint image detection from sweeping fingerprint sensors.

Sensors (Basel, Switzerland)
A sweeping fingerprint sensor converts fingerprints on a row by row basis through image reconstruction techniques. However, a built fingerprint image might appear to be truncated and distorted when the finger was swept across a fingerprint sensor at ...

Personalized keystroke dynamics for self-powered human--machine interfacing.

ACS nano
The computer keyboard is one of the most common, reliable, accessible, and effective tools used for human--machine interfacing and information exchange. Although keyboards have been used for hundreds of years for advancing human civilization, studyin...