Application of artificial neural networks for the rapid classification of archaeological ceramics by means of laser induced breakdown spectroscopy (LIBS)

Ramil, A.; Díaz, Ana Jesús López; Yáñez, A.

doi:10.1007/s00339-008-4481-7

Cited by 72 publications

(25 citation statements)

References 15 publications

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“…One of the examples of perceptron-type ANN application for LIBS which is also the closest to our case is one proposed by A. Ramil et al [9]. In their work they prepared an ANN for archeological ceramics spectra recognition.…”

Section: Perceptron Application For Libs Examplementioning

confidence: 91%

“…All of the samples were recognized correctly, though, the results for S11 and S20 were not absolutely unequivocal. The diagram is from [9].…”

Section: Perceptron Application For Libs Examplementioning

confidence: 99%

“…Based on the extensive literature [9,10,11] on the ANN LIBS applications we expect the Multilayer Perceptron (MLP) as the best for LIBS ITER-like materials data analysis. The MLP (Fig.…”

Section: Multilayer Perceptron Networkmentioning

confidence: 99%

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Computer methods for ITER–like materials LIBS diagnostics

Łepek

Gąsior

2014

SPIE Proceedings

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Recent development of Laser-Induced Breakdown Spectroscopy (LIBS) caused that this method is considered as the most promising for future diagnostic applications for characterization of the deposited materials in the International Thermonuclear Experimental Reactor (ITER), which is currently under construction. In this article the basics of LIBS are shortly discussed and the software for spectra analyzing is presented. The main software function is to analyze measured spectra with respect to the certain element lines presence. Some program operation results are presented. Correct results for graphite and aluminum are obtained although identification of tungsten lines is a problem. The reason for this is low tungsten lines intensity, and thus low signal to noise ratio of the measured signal. In the second part artificial neural networks (ANNs) as the next step for LIBS spectra analyzing are proposed. The idea is focused on multilayer perceptron network (MLP) with backpropagation learning method. The potential of ANNs for data processing was proved through application in several LIBS-related domains, e.g. differentiating ancient Greek ceramics (discussed). The idea is to apply an ANN for determination of W, Al, C presence on ITER-like plasma-facing materials.

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Section: Perceptron Application For Libs Examplementioning

confidence: 91%

“…All of the samples were recognized correctly, though, the results for S11 and S20 were not absolutely unequivocal. The diagram is from [9].…”

Section: Perceptron Application For Libs Examplementioning

confidence: 99%

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Computer methods for ITER–like materials LIBS diagnostics

Łepek

Gąsior

2014

SPIE Proceedings

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“…Moreover, LIBS is a very promising technique for the elemental analysis of many types of cultural heritage objects [3], such as pottery, sculptures, pigments of paintings, glass, calcified tissues, geological samples or metals; as proved before [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Comparative study on fast classification of brick samples by combination of principal component analysis and linear discriminant analysis using stand-off and table-top laser-induced breakdown spectroscopy

Vítková

Prokeš

Novotný

et al. 2014

Spectrochimica Acta Part B: Atomic Spectroscopy

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“…us, LIBS has been widely used for various applications, such as industry-oriented analysis [3], archaeological investigation [4], geological and environmental studies [5][6][7], and jewelry characterization [8]. Geological materials including rocks and minerals convey important information about particular geological environments, and this information can be extremely useful for studies such as determining mineral provenance, reservoir description, prospecting, and geochemical mapping [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Classification of Geological Samples Based on Soft Independent Modeling of Class Analogy Using Laser-Induced Breakdown Spectroscopy

Zhang

et al. 2018

Journal of Spectroscopy

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Laser-induced breakdown spectroscopy with soft independent modeling of class analogy is used in the identification of a large number of unprocessed geological samples having similar components in this study. Considering a variety of data from different samples, representative spectral regions representing the major components were extracted. In addition, principal component analysis was applied to remove noninformative variables from the spectrum. e unclassification rate, misclassification rate, and average correct classification rate for 25 types of geological samples were 1.2%, 4.7%, and 94.1%, respectively. ese results suggest that laser-induced breakdown spectroscopy using soft independent modeling of class analogy can be used to identify a wide variety of geological samples. Furthermore, we found that this approach can be used to identify spectral differences among similar sample types because of matrix effects and the trace element impurities.

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Application of artificial neural networks for the rapid classification of archaeological ceramics by means of laser induced breakdown spectroscopy (LIBS)

Cited by 72 publications

References 15 publications

Computer methods for ITER–like materials LIBS diagnostics

Computer methods for ITER–like materials LIBS diagnostics

Comparative study on fast classification of brick samples by combination of principal component analysis and linear discriminant analysis using stand-off and table-top laser-induced breakdown spectroscopy

Classification of Geological Samples Based on Soft Independent Modeling of Class Analogy Using Laser-Induced Breakdown Spectroscopy

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