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Convolutional neural network for skull recognition

Automatic skull identification systems play a vital role for forensic law authorities to recognize victim identity. Motivated by potential applications of these kinds of systems, this research aims to apply a pre-trained deep convolutional neural network (CNN) for face skull recognition. Basically,...

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Main Authors: Badr Lahasan, Badr Lahasan, Samma, Hussein
Format: Article
Language:English
Published: Penerbit UTM Press 2022
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/108819/1/HusseinSalemAli2022_ConvolutionalNeuralNetworkforSkullRecognition.pdf
http://eprints.utm.my/108819/
http://dx.doi.org/10.11113/ijic.v12n1.347
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spelling my.utm.1088192024-12-09T07:32:24Z http://eprints.utm.my/108819/ Convolutional neural network for skull recognition Badr Lahasan, Badr Lahasan Samma, Hussein QA75 Electronic computers. Computer science Automatic skull identification systems play a vital role for forensic law authorities to recognize victim identity. Motivated by potential applications of these kinds of systems, this research aims to apply a pre-trained deep convolutional neural network (CNN) for face skull recognition. Basically, the unknown skull image is fed to a pre-trained CNN network to extract a 1D feature vector, and then it will be matched with photos at database agencies to identify the closest match. To validate the proposed skull recognition system, it has been applied for a total of 13 skulls, and the reported results indicated a good was achieved. In addition, various CNN architectures were investigated, including shallow, medium, and deep CNN models. The best performance was reported from the shallow CNN model with a 92% recognition rate. Penerbit UTM Press 2022 Article PeerReviewed application/pdf en http://eprints.utm.my/108819/1/HusseinSalemAli2022_ConvolutionalNeuralNetworkforSkullRecognition.pdf Badr Lahasan, Badr Lahasan and Samma, Hussein (2022) Convolutional neural network for skull recognition. International Journal of Innovative Computing, 12 (1). pp. 55-58. ISSN 2180-4370 http://dx.doi.org/10.11113/ijic.v12n1.347 DOI : 10.11113/ijic.v12n1.347
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Badr Lahasan, Badr Lahasan
Samma, Hussein
Convolutional neural network for skull recognition
description Automatic skull identification systems play a vital role for forensic law authorities to recognize victim identity. Motivated by potential applications of these kinds of systems, this research aims to apply a pre-trained deep convolutional neural network (CNN) for face skull recognition. Basically, the unknown skull image is fed to a pre-trained CNN network to extract a 1D feature vector, and then it will be matched with photos at database agencies to identify the closest match. To validate the proposed skull recognition system, it has been applied for a total of 13 skulls, and the reported results indicated a good was achieved. In addition, various CNN architectures were investigated, including shallow, medium, and deep CNN models. The best performance was reported from the shallow CNN model with a 92% recognition rate.
format Article
author Badr Lahasan, Badr Lahasan
Samma, Hussein
author_facet Badr Lahasan, Badr Lahasan
Samma, Hussein
author_sort Badr Lahasan, Badr Lahasan
title Convolutional neural network for skull recognition
title_short Convolutional neural network for skull recognition
title_full Convolutional neural network for skull recognition
title_fullStr Convolutional neural network for skull recognition
title_full_unstemmed Convolutional neural network for skull recognition
title_sort convolutional neural network for skull recognition
publisher Penerbit UTM Press
publishDate 2022
url http://eprints.utm.my/108819/1/HusseinSalemAli2022_ConvolutionalNeuralNetworkforSkullRecognition.pdf
http://eprints.utm.my/108819/
http://dx.doi.org/10.11113/ijic.v12n1.347
_version_ 1818834053540872192
score 13.223943

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