Threat Target Classification Using Ann and SVM Based on a New Sensor Array System

Al-Qubaa, A. R.; Alshiha, Abeer A. Mohamad; Tian, Gui Yun

doi:10.2528/pierb14050704

Cited by 7 publications

(4 citation statements)

References 22 publications

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“…There is some also other previous research on the subject of metallic object classification using a WTMD portal. An approach based on EM imaging technology has been proposed by Al-Qubaa et al [15]. However, the used test set is limited, and although the results are not directly comparable, the reported classification accuracies seem lower than in our studies [4,5].…”

Section: Related Workcontrasting

confidence: 76%

Improving reliability for classification of metallic objects using a WTMD portal

Makkonen

Marsh

Vihonen

et al. 2015

Meas. Sci. Technol.

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In this paper, a walk-through metal detection (WTMD) portal is used for classification of metallic objects. The classification is based on the inversion of the magnetic polarisability tensor (tensor) of the object. The nature of bias and noise components in the tensor are examined by using real walk-through data, and consequently, a novel classifier is introduced. Furthermore, a novel method for detecting poorly inverted tensors is presented, enabling self-diagnostics for the WTMD portal. Based on the results, the novel methods increase the accuracy of metal object classification and have the potential to improve the reliability of a WTMD system.

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Section: Related Workcontrasting

confidence: 76%

Improving reliability for classification of metallic objects using a WTMD portal

Makkonen

Marsh

Vihonen

et al. 2015

Meas. Sci. Technol.

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“…Then, the correct identification becomes unlikely. Al-Qubba et al [8] built a giant magneto-resistive sensor. They used an artificial neural network and support vector machines to recognise threat objects.…”

Section: Research On Wtmd and Bs Devicesmentioning

confidence: 99%

Feasibility of Reducing Operator-to-Passenger Contact for Passenger Screening at the Airport with Respect to the Power Consumption of the System

Kierzkowski

Kisiel

2021

Energies

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So far, airport security screening has only been analysed in terms of efficiency, level of service, and protection against any acts of unlawful interference. Screening procedures have not yet addressed the need to limit operator-to-passenger contact. However, the pandemic situation (COVID-19) has shown that it is a factor that can be a key protection for the health of passengers and operators. The purpose of this paper was to analyse the feasibility of reducing contact between operators and passengers in the airport security screening system by process management with respect to the power consumption of the system. Experimental research was conducted on a real system. A computer simulation was applied to estimate system performance and power consumption. The paper identifies the important findings that expand upon previous knowledge. The results showed that there are two key factors: the experience of operators and proper system structure. These factors can significantly reduce the number of operator-to-passenger contacts and, in parallel, provide lower energy consumption of the system. The results obtained in this article showed that proper management improves the process by up to 37%. This approach expands the World Health Organization’s policy of prevention against COVID-19 and helps to ensure sustainable process management.

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“…SVM raises the data dimension and linearizes the data; meanwhile there is almost no increase in computational complexity. Therefore, SVM is especially suitable for small samples and some inherently nonlinear problems [19,20] . This should be attributed to the kernel function and its expansion theory.…”

Section: Samples and Experimental Setupmentioning

confidence: 99%

“…ANN has good nonlinear mapping ability, and has priority in solving nonlinear problems of systems with components interaction. Nowadays, neural networks with different structures have been applied to spectral analysis [20,21] . In this paper, the Radical Basis Function (RBF) network was used, which is a three-layer feed-forward networks.…”

Section: Samples and Experimental Setupmentioning

confidence: 99%

Classification and Discrimination of Minerals Using Laser Induced Breakdown Spectroscopy and Raman Spectroscopy

Zhang

Yan

et al. 2015

Plasma Sci. Technol.

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The classification and discrimination of minerals are important in geological research. The distribution of rocks and minerals may be inferred based on their identification, which is helpful for the investigation of some geological and environmental evolution problems, either on the earth or on other planets. LIBS and Raman spectra techniques have shown great advantages in simultaneous multi-component, in-situ, and non-destructive detection and they play an important role in rock composition analysis. In this presentation, six kinds of minerals (Gypsum, Spodumene, Barite, Haematite, Moonstone, and Labradorite) were detected by first using LIBS and Raman systems, and then several other methods (PCA, PLS-DA, ANN, and SVM) were used to evaluate the LIBS, Raman, and the fused LIBS/Raman data, respectively. The results indicate the superiority of the fused LIBS/Raman data in mineral classification, which stems from their complementary analysis abilities when studying element composition and structural features.

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Threat Target Classification Using Ann and SVM Based on a New Sensor Array System

Cited by 7 publications

References 22 publications

Improving reliability for classification of metallic objects using a WTMD portal

Improving reliability for classification of metallic objects using a WTMD portal

Feasibility of Reducing Operator-to-Passenger Contact for Passenger Screening at the Airport with Respect to the Power Consumption of the System

Classification and Discrimination of Minerals Using Laser Induced Breakdown Spectroscopy and Raman Spectroscopy

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