Paper Title
FashionAdvisorModelBasedonSkin Tone and Body Type

Abstract
In an era of personalized consumer experiences, the need for tailored fashion advicehasgrownsignificantly.ThisstudyoffersaFashionAdvisorModelcreated especiallyforindividualcustomersatadesignerstudio,offeringsuggestionsbased on a mix of body type, skin tone, and cultural fashion tastes.Using machine learningtechniqueslikeGANs,CNNs,anddecisiontrees,togetherwithskincolor recognition via the HSV color model, the model provides real-time individualized clothing recommendations. It customizes its suggestions based on user profiles using picture recognition and personal input, offering outfit options for both corporate and informal settings.These suggestions are further improved overtime by a feedback process, which further increases user happiness and accuracy. Thismodelis aprimeexample ofhowsophisticatedAIcanenhancefashion advice and provide consumers a customized, interactive, and one-of-a-kind style experience. Keywords - Fashion Recommendation, Skin Tone Detection, Body Type Classification,GANs, PersonalizedStyling,CNN,HSVColor Mode