Abstract:
Due to the advancement in deep learning models, they have established a
strong foothold in the field of medicine. Dentists are relying increasingly
on classification models that employ deep learning. Deep neural networks
(DNNs) are the most effective and prevalent machine learning models used
for a variety of image analysis tasks including image retrieval, image classi fication, object detection, and 3D analysis. They have reached performance
levels comparable to those of humans. DNNs are becoming increasingly com mon for roles like medical image processing, landmark/organ, localization,
cancer diagnosis, diabetic retinopathy detection, Covid-19 identification, and
teeth classification due to their success with natural images (such as images
captured from natural scenes, such as imagenet and CIFAR-10). Despite the
increase in the development of wise intelligent systems through the incorpo ration of deep structured networks, the vulnerability of such systems may be
compromised by the mere presence of an adversarial perturbation. In this
research, a new approach is proposed that will classify different teeth diseases
and also to improve accuracy the GANs has been implemented.
