Skin Disease Detection with Deep Learning
Nowadays, skin diseases are very common due to increasing bacterial attack, fungal infection, UVB rays due to the depleting ozone layer. So, if we can take preventive measures from early on, then we can increase the rate of recovery. For early detection, we proposed a method that uses computer vision based techniques to detect three kinds of dermatological skin diseases. We have trained our CNN model with the dataset of eight types of diseases, those are Acne, Basal Cell Carcinoma, Rosacea, Nevus, Melanoma, Eczema, Actinic Keratosis and Seborrheic keratosis. The system successfully detects these eight diseases with an accuracy rate of 95%
Authors
- Fariah Mahzabeen (ORCID: https://orcid.org/0000-0003-3135-3100)
- J. M. Shafi Ferdous (ORCID: https://orcid.org/0000-0002-7423-7890)
- Md. Arifur Rahman Akib
Institutions
- North South University (BD)
Publication Details
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1109/tencon61640.2024.10902760
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00