Face Skin Disease Classification Using Deep Learning Method (FSDC-DLM)

Abstract

Digital technology has greatly improved the detection and diagnosis of skin disorders affecting the face, including cancer and gum disease. Before training the model, we used a number of data pretreatment and augmentation procedures to make it more effective. Rosacea, eczema, basal cell carcinoma, acne, and actinic keratosis were among the skin disorders that the researchers hoped to identify by applying the Deep Learning Method (InceptionResNetV2). The recommended InceptionResNetV2 model achieves a higher accuracy rate than current best practices, at 98.05%.