Hair and Scalp Disease Detection using Machin...

Hair and Scalp Disease Detection using Machine Learning and Image Processing

Author Name : Prof. Rajeshwari P. Suryavanshi , Aishwarya Wanjari , Megha Mahajan , Tanaya Kachewar , Vedanti Khobragade

ABSTRACT In this study, a deep learning model built on the VGG (Visual Geometry Group) architecture is used to predict hair illnesses and offer individualized therapy recommendations. A prevalent dermatological issue, hair illnesses can significantly affect both a person's physical appearance and psychological health. Effective management depends on an early and correct diagnosis as well as personalized therapy suggestions. In this study, we constructed a convolutional neural network (CNN) model to interpret photos of hair and scalp conditions, which was inspired by the VGG architecture. A large and varied collection of hair disease photos, covering a variety of hair and scalp diseases, was used to train the model.