Forensic anthropology and human identification
The identification of missing persons is a global challenge. The number of found and unidentified bodies increases every year due to factors such as natural disasters (increasingly frequent due to climate change) and conflicts (wars, terrorism, etc.), among others.
Forensic medicine is the discipline that, among its main tasks, deals with the identification of human beings (living and dead). In particular, the specialty of forensic anthropology is more broadly conceived as the field of forensic evaluation of human remains, mostly skeletal, and their surroundings. When not enough information is available to apply other identification techniques such as DNA or fingerprinting, human identification based on forensic anthropology is the last chance to identify. On the other hand, the study of the skeleton is also considered the first stage in any forensic identification process. Before making an identification decision, the anthropologist must perform a biological profile of the remains, assigning sex, age, population affinity, etc.
This research line aims to exploit the capabilities of artificial intelligence (machine learning, deep-learning, computer vision, etc.) to facilitate human identification based on forensic anthropology.
Contact: Sergio Damas Arroyo
Related Researchers:
Letra: |
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Bermejo Nievas, Enrique | enrique.bermejoZ1da8EZo@decsai.ugr.es | Computational Intelligence Area, DaSCI Technology Applications Area | PhD |
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Cordón García, Óscar | ocordon@decsai.g6tZh@cuZVsRugr.es | DaSCI Technology Applications Area | PhD |
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Damas Arroyo, Sergio | sdamas@uekS.yz2xnv5gr.es | DaSCI Technology Applications Area | PhD |
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Mesejo Santiago, Pablo | pablomesejo9.m7TrHJVCG@gmail.com | DaSCI Technology Applications Area | PhD - Marie Curie |
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Ortíz García, Andrés | aortiz@icsDoNgXKGq.uma.es | DaSCI Technology Applications Area | PhD |
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Villar Castro, Pedro | pvillarcT@2oSbSN@ugr.es | Data Science and Big Data Area | PhD |
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Villar Castro, Pedro | pvillarctuqLUZ_f7@u@ugr.es | Data Science and Big Data Area | PhD |