Human Dental Age and Gender Assessment from Dental Radiographs Using Deep Convolutional Neural Network

Human gender and age identification play a prominent role in forensics, bio-archaeology, anthropology. Dental images provide indications used for the treatment or diagnosis of disease forensic investigation. Numerous dental techniques come with specific boundaries, namely minimum reliability accuracy. Gender approaches are not widely researched, whereas effectiveness accuracy classification practical very minimal. Drawbacks existing system considered formulation proposed approach. Deep learning can effectively rectify issues drawbacks other classifiers. The performance classifier enhanced deep convolutional neural network. fuzzy C-Means Clustering approach is segmentation, Ant Lion Optimization optimal feature score selection. selected features classified using network (DCNN). technique investigated classifiers, DCNN outperforms achieves 91.7% 91% age, respectively.