An Efficient Approach for Skin Disease Detection using Deep Learning

Skin diseases are mostly caused by fungal infection, bacteria, allergy, or viruses, etc. The lasers advancement and photonics based medical technology is used in diagnosis of the skin diseases quickly and accurately. But the medical equipment for such diagnosis is limited and mostly expensive. However, using an image-based diagnosis system can help in reducing both time and cost. Image processing and Deep learning techniques can be combined together which helps in detection of skin disease at an initial stage. On the other hand, feature extraction plays a key role in classification of skin diseases. We propose an efficient approach for detecting skin disease using deep learning. The proposed system enables detecting skin disease with 85.14% accuracy which is higher than that of the existing models.