Skin Disease Analysis With Limited Data in Particular Rosacea: A Review and Recommended Framework

Recently, the rapid advancements in Deep Learning and Computer Vision technologies have introduced a new exciting era field of skin disease analysis. However, there are certain challenges roadmap towards developing such for real-life applications that must be investigated. This study considers one key data acquisition computation, viz. scarcity. Data scarcity is central problem acquiring medical images applying machine learning techniques to train Convolutional Neural Networks diagnosis. The main objective this explore possible methods deal with improve diagnosis small datasets. few lamentably neglected conditions as rosacea an excellent instance possibilities improving computer-aided With mind, explored discussed include Generative Adversarial Networks, Meta-Learning, Few-Shot classification, 3D face modelling. Furthermore, existing studies based on considered, volume implementation choices. Some future research directions recommended.