scholarly journals Automated Border Control Systems: Biometric Challenges and Research Trends

2015 ◽  
pp. 11-20 ◽  
Author(s):  
Ruggero Donida Labati ◽  
Angelo Genovese ◽  
Enrique Muñoz ◽  
Vincenzo Piuri ◽  
Fabio Scotti ◽  
...  
Keyword(s):  
Control Systems ◽  
Research Trends ◽  
Border Control

Control Systems in Manufacturing

1994 ◽  
Author(s):  
Mruthyunjaya S. Telagi ◽  
Athamaram H. Soni
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Fuzzy Logic ◽  
Control Systems ◽  
Research Trends ◽  
Future Research ◽  
Cerebellar Model Articulation Controller ◽  
Manufacturing Environment ◽  
The Future ◽  
Planar Robot

Abstract This paper reviews different control methodologies applied in manufacturing environment. Since comparatively newer control methodologies like — Neural networks, Fuzzy logic, and Cerebellar model articulation controller have gained more research interests in recent years, they have been dealt in more detail. With this, we have presented application of neural network for endeffector positioning of three degree planar robot and results have been evaluated. Finally the future research trends in these areas have been discussed.

scholarly journals Enhancing the Performance of Multimodal Automated Border Control Systems

2016 ◽  
Author(s):  
Abhinav Anand ◽  
Ruggero Donida Labati ◽  
Angelo Genovese ◽  
Enrique Munoz ◽  
Vincenzo Piuri ◽  
...  
Keyword(s):  
Control Systems ◽  
Border Control

scholarly journals Convolutional Neural Network Approach for Multispectral Facial Presentation Attack Detection in Automated Border Control Systems

Entropy ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. 1296
Author(s):  
M. Araceli Sánchez-Sánchez ◽  
Cristina Conde ◽  
Beatriz Gómez-Ayllón ◽  
David Ortega-DelCampo ◽  
Aristeidis Tsitiridis ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Control Systems ◽  
Near Infrared ◽  
Attack Detection ◽  
Added Value ◽  
Border Control ◽  
Security Risk ◽  
Neural Network Approach ◽  
Presentation Attack Detection

Automated border control systems are the first critical infrastructure point when crossing a border country. Crossing border lines for unauthorized passengers is a high security risk to any country. This paper presents a multispectral analysis of presentation attack detection for facial biometrics using the learned features from a convolutional neural network. Three sensors are considered to design and develop a new database that is composed of visible (VIS), near-infrared (NIR), and thermal images. Most studies are based on laboratory or ideal conditions-controlled environments. However, in a real scenario, a subject’s situation is completely modified due to diverse physiological conditions, such as stress, temperature changes, sweating, and increased blood pressure. For this reason, the added value of this study is that this database was acquired in situ. The attacks considered were printed, masked, and displayed images. In addition, five classifiers were used to detect the presentation attack. Note that thermal sensors provide better performance than other solutions. The results present better outputs when all sensors are used together, regardless of whether classifier or feature-level fusion is considered. Finally, classifiers such as KNN or SVM show high performance and low computational level.

Dynamic facial presentation attack detection for automated border control systems

2020 ◽  
Vol 92 ◽  
pp. 101744
Author(s):  
David Ortega ◽  
Alberto Fernández-Isabel ◽  
Isaac Martín de Diego ◽  
Cristina Conde ◽  
Enrique Cabello
Keyword(s):  
Control Systems ◽  
Attack Detection ◽  
Border Control ◽  
Presentation Attack Detection

scholarly journals Advanced design of Automated Border Control gates: Biometric system techniques and research trends

2015 ◽  
Author(s):  
Ruggero Donida Labati ◽  
Angelo Genovese ◽  
Enrique Munoz ◽  
Vincenzo Piuri ◽  
Fabio Scotti ◽  
...  
Keyword(s):  
Research Trends ◽  
Border Control ◽  
Biometric System
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