Classification of Dental Disease Through Various CNN Techniques and Performance Analysis

The major cause underlying losing teeth is dental caries, a progressive bacteria-related infection. Poor dental hygiene, which also results in a number of dental disorders, is the cause of this. For children's dental health, it would be extremely beneficial if caries could be diagnosed at a young age via a system. This is that acute caries can cause awkwardness and infection, which may lead to pulling teeth. Researchers are most concerned with the early identification and detection of oral caries. Dental professionals frequently employ soft computing approaches to speed up and simplify diagnoses. Through the use of digital images, dental caries is to be identified early on in this research, allowing for simple and efficient treatment. For this suggested work, the convolution neural network is applied as our deep learning architecture. It has trained various CNN models, including Resnet50. The training, validation and testing phases were completed using a binary dataset containing images with and without caries.