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Pattern recognition techniques for provenance classification of archaeological ceramics using ultrasounds

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Pattern recognition techniques for provenance classification of archaeological ceramics using ultrasounds

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dc.contributor.author Salazar Afanador, Addisson es_ES
dc.contributor.author Safont Armero, Gonzalo es_ES
dc.contributor.author Vergara Domínguez, Luís es_ES
dc.contributor.author Vidal, Enrique es_ES
dc.date.accessioned 2021-11-05T12:27:18Z
dc.date.available 2021-11-05T12:27:18Z
dc.date.issued 2020-07 es_ES
dc.identifier.issn 0167-8655 es_ES
dc.identifier.uri http://hdl.handle.net/10251/176085
dc.description.abstract [EN] This paper presents a novel application of pattern recognition to the provenance classification of archae- ological ceramics. This is a challenging problem for archaeologists, which involves assigning a making location to a fragment of archaeological pottery that was found along with other fragments of pieces made in different distant locations from the find. The pieces look very similar to each other and, often, other contextual information about the use of the pieces cannot be used due to the small size of the fragments. Current standard methods to solve this problem are limited since they are time consuming, require costly equipment, and can lead to the destruction of a part of the pieces. The proposed method overcome those limitations using non-destructive ultrasonic testing and incorporates versatile data anal- ysis through advanced pattern recognition techniques. Those techniques include the following: feature ranking, sample augmentation, semi-supervision based on active learning; and optimal fusion. This latter is based in the concept of alpha integration, which allows optimal fitting of the fusion model parameters. Different provenance classification problems are showcased: provenance classification of terra sigillata ce- ramic pieces from Aretina, Northern Italy and Sud-Gaul origins; and provenance classification of Iberian ceramic pieces from archaeological sites of Paterna, and Les Jovaes in Valencia, Spain. We demonstrate that the proposed fusion-based method achieves the best results, in terms of balanced classification ac- curacy and F1 score, compared with competitive methods like linear discriminant analysis, random forest, and support vector machine. Experiments for simulating small sample sizes and uncertainty in labeling of the pieces are included. In addition, the paper provides a design of a practical specialized device that could be used in different applications of archaeological ceramic classification. es_ES
dc.description.sponsorship This work was supported by Spanish Administration and European Union under grant TEC2017-84743-P. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Pattern Recognition Letters es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Decision fusion es_ES
dc.subject Semi-supervised active learning es_ES
dc.subject Feature ranking es_ES
dc.subject Ultrasounds es_ES
dc.subject Archaeological ceramics es_ES
dc.subject Provenance Classification es_ES
dc.subject Pattern recognition es_ES
dc.subject.classification TEORIA DE LA SEÑAL Y COMUNICACIONES es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Pattern recognition techniques for provenance classification of archaeological ceramics using ultrasounds es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.patrec.2020.04.013 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//TEC2017-84743-P-AR//METODOS INFORMADOS PARA LA SINTESIS DE SEÑALES/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia es_ES
dc.description.bibliographicCitation Salazar Afanador, A.; Safont Armero, G.; Vergara Domínguez, L.; Vidal, E. (2020). Pattern recognition techniques for provenance classification of archaeological ceramics using ultrasounds. Pattern Recognition Letters. 135:441-450. https://doi.org/10.1016/j.patrec.2020.04.013 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.patrec.2020.04.013 es_ES
dc.description.upvformatpinicio 441 es_ES
dc.description.upvformatpfin 450 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 135 es_ES
dc.relation.pasarela S\418759 es_ES
dc.contributor.funder AGENCIA ESTATAL DE INVESTIGACION es_ES


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