018

Title:

AUTOMATIC DIAGNOSIS OF ACNE AND ROSACEA USING DEEP LEARNING

Discipline: Computer Vision and Deep Learning

Presenter:

Firas Gerges

Abstract:

Acne and Rosacea are two common skin diseases that affect many people in United States. These two skin conditions can result in similar symptoms, which leads patients to mistake their case. In this paper, we aim to develop a model that can efficiently differentiate between these two skin conditions. A deep learning model is proposed in order to automatically distinguish Rosacea from Acne cases using infected skin images. Using image augmentation, the size of the original dataset can be enlarged. Experimental results show that our model achieves a very high performance with an average testing accuracy of 99%.

Author(s):

Firas Gerges, Dr. Frank Y. Shih

Funding Acknowledgements:

nan