• Kruthika LP
• Poornima RM
• NK Vidya
• Poornima R

Skin diseases are common diseases that may be caused due to allergies, viruses, bacteria, fungal infections, etc. Though there’s a rapid advancement in medical technology to diagnose skin disease quickly and accurately it is still limited due to its cost. But analyzing and predicting the disease using a deep learning approach has come in handy. This project is mainly proposed by CNN. In this approach three image recognition architectures are used, namely Inception V3 for image recognition, InceptionResnet V2 is a CNN that is used in training more than a million images from the image net database and MobileNet is used for embedded vision applications with certain modifications to predict the skin diseases based on maximum voting from the three networks. The main objective is to get maximum accuracy in predicting skin disease.

CNN, Inception V2, Inception V3, MobileNET

"Automated Skin Disease Identification Using Deep Learning Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.n515-n531, May-2023, Available :http://www.jetir.org/papers/JETIR2305D75.pdf

"Automated Skin Disease Identification Using Deep Learning Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppn515-n531, May-2023, Available at : http://www.jetir.org/papers/JETIR2305D75.pdf