dc.contributor.author | Mesejo, Pablo | |
dc.contributor.author | Martos, Rubén | |
dc.contributor.author | Ibáñez, Oscar | |
dc.contributor.author | Novo Buján, Jorge | |
dc.contributor.author | Ortega Hortas, Marcos | |
dc.date.accessioned | 2020-09-17T15:29:14Z | |
dc.date.available | 2020-09-17T15:29:14Z | |
dc.date.issued | 2002-07-08 | |
dc.identifier.citation | Mesejo, P.; Martos, R.; Ibáñez, Ó.; Novo, J.; Ortega, M. A Survey on Artificial Intelligence Techniques for Biomedical Image Analysis in Skeleton-Based Forensic Human Identification. Appl. Sci. 2020, 10, 4703. | es_ES |
dc.identifier.issn | 2076-3417 | |
dc.identifier.uri | http://hdl.handle.net/2183/26210 | |
dc.description.abstract | [Abstract]
This paper represents the first survey on the application of AI techniques for the analysis of biomedical images with forensic human identification purposes. Human identification is of great relevance in today’s society and, in particular, in medico-legal contexts. As consequence, all technological advances that are introduced in this field can contribute to the increasing necessity for accurate and robust tools that allow for establishing and verifying human identity. We first describe the importance and applicability of forensic anthropology in many identification scenarios. Later, we present the main trends related to the application of computer vision, machine learning and soft computing techniques to the estimation of the biological profile, the identification through comparative radiography and craniofacial superimposition, traumatism and pathology analysis, as well as facial reconstruction. The potentialities and limitations of the employed approaches are described, and we conclude with a discussion about methodological issues and future research. | es_ES |
dc.description.sponsorship | Ministerio de Ciencia, Innovación y Universidades; PGC2018-101216-B-I00 | es_ES |
dc.description.sponsorship | Ministerio de Ciencia, Innovación y Universidades; RTI2018-095894-B-I00 | es_ES |
dc.description.sponsorship | Junta de Andalucía; P18-FR-4262 | es_ES |
dc.description.sponsorship | Instituto de Salud Carlos III; DTS18/00136 | es_ES |
dc.description.sponsorship | Ministerio de Ciencia, Innovación y Universidades; EXP-00122609/SNEO-20191236 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G 2019/01 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | M D P I AG | es_ES |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/746592 | es_ES |
dc.relation.uri | https://doi.org/10.3390/app10144703 | es_ES |
dc.rights | Atribución 4.0 España | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/es/ | * |
dc.subject | Forensic medicine | es_ES |
dc.subject | Forensic anthropology | es_ES |
dc.subject | Forensic imaging | es_ES |
dc.subject | Skeleton-based forensic identification | es_ES |
dc.subject | Machine learning | es_ES |
dc.subject | Computer vision | es_ES |
dc.subject | Soft computing | es_ES |
dc.subject | Biological profiling | es_ES |
dc.subject | Comparative radiography | es_ES |
dc.subject | Craniofacial identification | es_ES |
dc.title | A Survey on Artificial Intelligence Techniques for Biomedical Image Analysis in Skeleton-Based Forensic Human Identification | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Applied Sciences | es_ES |
UDC.volume | 14 | es_ES |
UDC.issue | 10 | es_ES |
UDC.startPage | 4703 | es_ES |