With the increasing incidence of skin cancers such as Basal Cell Carcinoma (BCC), Malignant Melanoma (MM), and Squamous Cell Carcinoma (SCC), the field of dermatology struggles to meet the demand in early diagnosis. Creating a necessity for a portable solution that is both easy to use and cost effective. This study investigates robust Artificial Intelligence (AI)-powered image recognition methods to diagnose skin diseases. Directly comparing different forms of AI such as Convolutional Neural Networks (CNN), and Deep Learning networks (DL). With a special focus on accuracy, sensitivity, and specificity. Aiming to indicate a recognition algorithm that can be implemented reliably. Finding that a DL (IMLT-DL) method would be both effective and easy to implement in an application.