Human gender prediction based on deep transfer learning from panoramic dental radiograph images
Yükleniyor...
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
International Information and Engineering Technology Association
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Panoramic Dental Radiography (PDR) image processing is one of the most extensively used
manual methods for gender determination in forensic medicine. With the assistance of the
PDR images, a person's biological gender determination can be performed through
analyzing skeletal structures expressing sexual dimorphism. Manual approaches require a
wide range of mandibular parameter measurements in metric units. Besides being timeconsuming, these methods also necessitate the employment of experienced professionals. In
this context, deep learning models are widely utilized in the auto-analysis of radiological
images nowadays, owing to their high processing speed, accuracy, and stability. In our
study, a data set consisting of 24,000 dental panoramic images was prepared for binary
classification, and the transfer learning method was used to accelerate the training and
increase the performance of our proposed DenseNet121 deep learning model. With the
transfer learning method, instead of starting the learning process from scratch, the existing
patterns learned beforehand were used. Extensive comparisons were made using deep
transfer learning (DTL) models VGG16, ResNet50, and EfficientNetB6 to assess the
classification performance of the proposed model in PDR images. According to the findings
of the comparative analysis, the proposed model outperformed the other approaches by
achieving a success rate of 97.25% in gender classification.
Açıklama
Anahtar Kelimeler
DenseNet121, Deep convolutional neural network, Deep transfer learning, Gender prediction, Panoramic dental radiograph
Kaynak
Traitement du Signal
WoS Q Değeri
Q3
Scopus Q Değeri
Q3
Cilt
39
Sayı
5
Künye
Ataş, İ. (2022). Human gender prediction based on deep transfer learning from panoramic dental radiograph images. Traitement du Signal, 39(5), 1585-1595.
