Modeling of Human Skin by the Use of Deep Learning - Xin Xiong; Xuexun Guo; Yiping Wang (Complexity)
Deep learning (DL) has matured well over time and resonated in various domains of computer applications. Pattern recognition gets more attention in machine learning field to take advantage of data available for modern life. Recognition by using the technology performance is worthy in terms of skin and other human features; this research tries to extract useful features from the skin and then classify these features under certain condition. The main objective of this study is to detect the skin diseases early and classify them for correct treatment. Using improved classifier (ISVM) to be adaptive with requirements of our task, many advantages can be got with this technique and it is useful in the fields of medicine, human health care, and diagnosis and life threat. Applying good classifier with best feature selection achieved good result in terms of accuracy, 95%, and recognition rate, 93%. This study concluded that adopting best strategy in selecting features and classification yields better prediction in emergency case before medicating the patient even during treatment.