Arshad, Ariba Noor  <br/><br/>
Skintify - A Skincare Product Recommendation Application / 
Ariba Noor Arshad, Aymen Fatima, Mubashir Hussain Shah, Saman Khalid. 
 - MCS, NUST   Rawalpindi   2024 
 - 147 p 
<br/><br/>This thesis introduces Skintify, an innovative mobile application designed to revolutionize the<br/>way individuals select skincare products. By harnessing the power of state-of-the-art<br/>technologies, including machine learning and image processing, Skintify offers personalized<br/>skincare recommendations uniquely tailored to various users. The application analyzes the skin<br/>type of the user by processing user facial images. This comprehensive analysis allows Skintify to<br/>recommend skincare products that precisely meet the individual needs of the user, thus providing<br/>a customized skincare regimen. This thesis details the development process of Skintify, from<br/>conceptualization to implementation, including the technological challenges encountered and the<br/>solutions employed. It details the prepared application that employs our trained model with a<br/>validation accuracy of 82.91%. Through Skintify, this work demonstrates the feasibility and<br/>effectiveness of applying advanced technological solutions to personal care, highlighting a<br/>significant step forward in the intersection of technology and personal health and wellness. 
<br/><br/><label>Subjects--Topical Terms: </label><br/>UG BESE
<br/><br/><label>Subjects--Geographic Terms: </label><br/>BESE-26 
<br/><br/><label>Dewey Class. No.: </label>005.1,ARS