• T. R. Arunkumar
• Dr. H. S. Jayanna

In this paper, the authors present an approach of classification of different types of psoriasis using machine learning.The main objective of the work is to classify the given psoriasis image into one of the classes of inverse psoriasis, nail psoriasis, plaque psoriasis, erethrodermic psoriasis, guttate psoriasis and pustular psoriasis. Convolution neural networks are used in the classification. The approach consumes less memory and can be deployed easily on hand held devices where processing capability is a constraint. In the initial stage, pre traind weights are used for the classification where the results were not promising. As the neural network is trained on input data images, the performance of the neural network is improved to 89%.

Convolution neural networks, Psoriasis, Accuracy, Keras.

"Classification of Different Types of Psoriasis Using Machine Learning.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.1437-1439, June-2019, Available :http://www.jetir.org/papers/JETIR1908D82.pdf

"Classification of Different Types of Psoriasis Using Machine Learning.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp1437-1439, June-2019, Available at : http://www.jetir.org/papers/JETIR1908D82.pdf