Abstract
Dental disease has become all too common in today’s fast-paced environment. Other thanthat, dental covers many things in the mouth such as the jaw, gums, teeth, and many more. Dental diseases include dental caries (tooth decay), periodontal diseases, tooth loss, oral malignancies, and many others. All these diseases will have a negative impact on persons who suffer from toothache. Aside from that, because the dental disease is placedin the person’s mouth, it is difficult to notice. As a result, natural eyes cannot be used andmust be replaced by medical tools. Because of that, the assistance of a dentist is critical. Indeed, due to technology nowadays, dental diseases may now be detected using Convolutional Neural Networks (CNN). Convolutional Neural Networks (CNN) are a type of artificial neural network that is commonly used in the field of Artificial Intelligence (AI). Many types of algorithms can be used for detection such as Support Vector Machines (SVM), Recurrent Neural Networks (RNNs), and many more but CNN shows the best result and accuracy which is 99%.
Metadata
Item Type: | Thesis (Degree) |
---|---|
Creators: | Creators Email / ID Num. Kamallul Ariffin, Faiznur 2022900721 |
Contributors: | Contribution Name Email / ID Num. Thesis advisor Mohamad, Norizan UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Neural networks (Computer science) |
Divisions: | Universiti Teknologi MARA, Terengganu > Kuala Terengganu Campus |
Programme: | Bachelor of Computer Science (Hons) |
Keywords: | Dental Disease, Convolutional Neural Networks (CNN) |
Date: | 2024 |
URI: | https://ir.uitm.edu.my/id/eprint/95551 |
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