Gender Identification Using Mandibular Morphometric Parameters and PCA-NN Classifier Algorithm on Panoramic Radiographs
Gender identification is urgently required to reveal the deceased person’s identity in several proximity conditions such as disasters, accidents, and violence. The mandible bone has been explored in the field of forensic odontology for the human gender identification. Dental panoramic radiography h...
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Fakultas Kedokteran Gigi Universitas Airlangga
2021
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id-langga.1127382021-12-07T04:09:40Z https://repository.unair.ac.id/112738/ Gender Identification Using Mandibular Morphometric Parameters and PCA-NN Classifier Algorithm on Panoramic Radiographs Agung Sosiawan, - Dian Agustin Wahjuningrum, - Arofi Kurniawan, - Justiawan, - Rafina Destiarti Ainul, - An’nisaa Chusida, - Aspalilah Alias, - R Medicine RK Dentistry Gender identification is urgently required to reveal the deceased person’s identity in several proximity conditions such as disasters, accidents, and violence. The mandible bone has been explored in the field of forensic odontology for the human gender identification. Dental panoramic radiography has become one of the routine procedures at medical hospitals as part of primary investigations. Untuk kepentingan submit jurna F1000 research Fakultas Kedokteran Gigi Universitas Airlangga 2021 Other NonPeerReviewed text id https://repository.unair.ac.id/112738/1/dataset%20Dean.pdf Agung Sosiawan, - and Dian Agustin Wahjuningrum, - and Arofi Kurniawan, - and Justiawan, - and Rafina Destiarti Ainul, - and An’nisaa Chusida, - and Aspalilah Alias, - (2021) Gender Identification Using Mandibular Morphometric Parameters and PCA-NN Classifier Algorithm on Panoramic Radiographs. Fakultas Kedokteran Gigi Universitas Airlangga. |
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Universitas Airlangga |
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Universitas Airlangga Library |
| continent |
Asia |
| country |
Indonesia Indonesia |
| content_provider |
Universitas Airlangga Library |
| collection |
UNAIR Repository |
| language |
Indonesian |
| topic |
R Medicine RK Dentistry |
| spellingShingle |
R Medicine RK Dentistry Agung Sosiawan, - Dian Agustin Wahjuningrum, - Arofi Kurniawan, - Justiawan, - Rafina Destiarti Ainul, - An’nisaa Chusida, - Aspalilah Alias, - Gender Identification Using Mandibular Morphometric Parameters and PCA-NN Classifier Algorithm on Panoramic Radiographs |
| description |
Gender identification is urgently required to reveal the deceased person’s identity in several proximity conditions such as disasters, accidents, and violence. The mandible bone has been explored in the field of forensic odontology for the human gender identification. Dental panoramic radiography has become one of the routine procedures at medical hospitals as part of primary investigations.
Untuk kepentingan submit jurna F1000 research |
| format |
Other NonPeerReviewed |
| author |
Agung Sosiawan, - Dian Agustin Wahjuningrum, - Arofi Kurniawan, - Justiawan, - Rafina Destiarti Ainul, - An’nisaa Chusida, - Aspalilah Alias, - |
| author_facet |
Agung Sosiawan, - Dian Agustin Wahjuningrum, - Arofi Kurniawan, - Justiawan, - Rafina Destiarti Ainul, - An’nisaa Chusida, - Aspalilah Alias, - |
| author_sort |
Agung Sosiawan, - |
| title |
Gender Identification Using Mandibular Morphometric Parameters and PCA-NN Classifier Algorithm on Panoramic Radiographs |
| title_short |
Gender Identification Using Mandibular Morphometric Parameters and PCA-NN Classifier Algorithm on Panoramic Radiographs |
| title_full |
Gender Identification Using Mandibular Morphometric Parameters and PCA-NN Classifier Algorithm on Panoramic Radiographs |
| title_fullStr |
Gender Identification Using Mandibular Morphometric Parameters and PCA-NN Classifier Algorithm on Panoramic Radiographs |
| title_full_unstemmed |
Gender Identification Using Mandibular Morphometric Parameters and PCA-NN Classifier Algorithm on Panoramic Radiographs |
| title_sort |
gender identification using mandibular morphometric parameters and pca-nn classifier algorithm on panoramic radiographs |
| publisher |
Fakultas Kedokteran Gigi Universitas Airlangga |
| publishDate |
2021 |
| url |
https://repository.unair.ac.id/112738/1/dataset%20Dean.pdf https://repository.unair.ac.id/112738/ |
| _version_ |
1718988173139247104 |