Gender classification using a PSO-based feature selection and optimised BPNN in forensic anthropology
Gender classification is a crucial task in most forensic cases.In most cases, skeleton remains are employed and there are different parts of human skeleton available for the classification process.Every part of skeleton contains different types of features which benefits toward gender classification...
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my.utm.266352022-02-28T13:25:26Z http://eprints.utm.my/id/eprint/26635/ Gender classification using a PSO-based feature selection and optimised BPNN in forensic anthropology Hairuddin, Nurul Liyana Yusuf, Lizawati Mi Othman, Mohd. Shahizan Nasien, Dewi QA75 Electronic computers. Computer science T58.5-58.64 Information technology Gender classification is a crucial task in most forensic cases.In most cases, skeleton remains are employed and there are different parts of human skeleton available for the classification process.Every part of skeleton contains different types of features which benefits toward gender classification.However, some features cannot contribute toward classification as features carry no information on gender.Hence, this article proposed a particle swarm optimisation-based (PSO) feature selection and optimised BPNN model as a gender classification framework.Initially, PSO selects the most significant features that lead to an accurate classification process.In the BPNN process, the parameter tuning based on cross-validation technique is applied where the model is able to find a good combination of learning rate and momentum.This article utilised data from Goldman Osteometric dataset, Clavicle collection, and George Murray Black collection.The result shows that the accuracy of gender classification is improved for every dataset via the proposed framework. Inderscience Publishers 2021-07 Article PeerReviewed Hairuddin, Nurul Liyana and Yusuf, Lizawati Mi and Othman, Mohd. Shahizan and Nasien, Dewi (2021) Gender classification using a PSO-based feature selection and optimised BPNN in forensic anthropology. International Journal of Computer Aided Engineering and Technology, 15 (2-3). pp. 232-242. ISSN 1757-2657 http://dx.doi.org/10.1504/IJCAET.2021.117133 DOI:10.1504/IJCAET.2021.117133 |
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QA75 Electronic computers. Computer science T58.5-58.64 Information technology Hairuddin, Nurul Liyana Yusuf, Lizawati Mi Othman, Mohd. Shahizan Nasien, Dewi Gender classification using a PSO-based feature selection and optimised BPNN in forensic anthropology |
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Gender classification is a crucial task in most forensic cases.In most cases, skeleton remains are employed and there are different parts of human skeleton available for the classification process.Every part of skeleton contains different types of features which benefits toward gender classification.However, some features cannot contribute toward classification as features carry no information on gender.Hence, this article proposed a particle swarm optimisation-based (PSO) feature selection and optimised BPNN model as a gender classification framework.Initially, PSO selects the most significant features that lead to an accurate classification process.In the BPNN process, the parameter tuning based on cross-validation technique is applied where the model is able to find a good combination of learning rate and momentum.This article utilised data from Goldman Osteometric dataset, Clavicle collection, and George Murray Black collection.The result shows that the accuracy of gender classification is improved for every dataset via the proposed framework. |
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Article |
author |
Hairuddin, Nurul Liyana Yusuf, Lizawati Mi Othman, Mohd. Shahizan Nasien, Dewi |
author_facet |
Hairuddin, Nurul Liyana Yusuf, Lizawati Mi Othman, Mohd. Shahizan Nasien, Dewi |
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Hairuddin, Nurul Liyana |
title |
Gender classification using a PSO-based feature selection and optimised BPNN in forensic anthropology |
title_short |
Gender classification using a PSO-based feature selection and optimised BPNN in forensic anthropology |
title_full |
Gender classification using a PSO-based feature selection and optimised BPNN in forensic anthropology |
title_fullStr |
Gender classification using a PSO-based feature selection and optimised BPNN in forensic anthropology |
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Gender classification using a PSO-based feature selection and optimised BPNN in forensic anthropology |
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gender classification using a pso-based feature selection and optimised bpnn in forensic anthropology |
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Inderscience Publishers |
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2021 |
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http://eprints.utm.my/id/eprint/26635/ http://dx.doi.org/10.1504/IJCAET.2021.117133 |
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