Convolutional neural networks (CNNs) are used to obtain feature maps from panoramic radiographs
We use U-net architecture in our image segmentation step. The u-net is convolutional network architecture for fast and precise segmentation of images.
We used Naïve Bayes in classification step for its:
- It is easy and fast to predict the class of the test data set. It also performs well in multi-class prediction.
- When assumption of independence holds, a Naive Bayes classifier performs better compare to other models like logistic regression and you need less training data.
- It performs well in case of categorical input variables compared to numerical variable(s)