Application of deep learning neural network to create a multi-class identifier to detect and categorize periodontal diseases
Keywords:
Convolution Neural Network (CNN), Multi-class classification, Periodontal diseases, Early diagnosisAbstract
Periodontal diseases is the major cause of bad breath and loss of tooth in adults worldwide. The comprehensive intention of the present study is to detect and categorize the type of periodontal diseases. In order to achieve the objective a Convolution Neural Network (CNN) model is proposed in the study. The proposed CNN model is built using the Tensorflow framework which is coded in python 3.8. The proposed model is trained using 3241 images of periodontal and non-periodontal diseases. The CNN model is tested using 90 images. The training and testing accuracy of the CNN model is 97.82% and 73.61% respectively whereas the loss computed by Mean Squre Error (MSE) for training and testing is 0.07 and 0.006 respectively.
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