dc.contributor.author | Mesejo Santiago, Pablo | |
dc.contributor.author | Martos, Rubén | |
dc.contributor.author | Ibáñez, Óscar | |
dc.contributor.author | Novo, Jorge | |
dc.contributor.author | Ortega, Marcos | |
dc.date.accessioned | 2020-09-10T10:41:03Z | |
dc.date.available | 2020-09-10T10:41:03Z | |
dc.date.issued | 2020-07-08 | |
dc.identifier.citation | Mesejo, P., Martos, R., Ibáñez, Ó., Novo, J., & Ortega, M. (2020). A Survey on Artificial Intelligence Techniques for Biomedical Image Analysis in Skeleton-Based Forensic Human Identification. Applied Sciences, 10(14), 4703. [doi: 10.3390/app10144703] | es_ES |
dc.identifier.uri | http://hdl.handle.net/10481/63371 | |
dc.description.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 | Spanish Ministry of Science, Innovation and Universities | es_ES |
dc.description.sponsorship | European Union (EU)
PGC2018-101216-B-I00 | es_ES |
dc.description.sponsorship | Regional Government of Andalusia under grant EXAISFI
P18-FR-4262 | es_ES |
dc.description.sponsorship | Instituto de Salud Carlos III | es_ES |
dc.description.sponsorship | European Union (EU)
DTS18/00136 | es_ES |
dc.description.sponsorship | European Commission H2020-MSCA-IF-2016 through the Skeleton-ID Marie Curie Individual Fellowship
746592 | es_ES |
dc.description.sponsorship | Spanish Ministry of Science, Innovation and Universities-CDTI, Neotec program 2019
EXP-00122609/SNEO-20191236 | es_ES |
dc.description.sponsorship | European Union (EU) | es_ES |
dc.description.sponsorship | Xunta de Galicia
ED431G 2019/01 | es_ES |
dc.description.sponsorship | European Union (EU)
RTI2018-095894-B-I00 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.rights | Atribución 3.0 España | * |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/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 | journal article | es_ES |
dc.rights.accessRights | open access | es_ES |
dc.identifier.doi | 10.3390/app10144703 | |