Abstract:
Skin diseases affect millions of people. These diseases often have hidden dangers that cause self-doubt, depression, and skin cancer. Skin disease affects 30%–70% of people, according to WHO. Most don’t understand skin disease classification.
We created a CNN-based Skin Disease Detection System. This project aims to help the average person understand the disease affecting their skin and prepare for its treatment, as well as help the doctor diagnose cancer faster and more accurately.
Logging in requires registration. The user uploads the image after logging in, and the system automatically detects the skin disease class. View doctors for diagnosis. The system displays the disease class to doctors. User feedback is allowed.
The admin logs in. They can view users, update, delete, and view doctors. They can also see user feedback.
A Convolutional Neural Network with Batch Normalization and an Adam optimizer was used. Kaggle dataset. Diseases detected include: Acne, Rosacea, Actinic Keratosis, Basal Cell Carcinoma, Melanoma, Dysplastic Nevi, Moles, and other malignant lesions.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
Did you like this final year project?
To download this project Code with thesis report and project training... Click Here
