This research aims to develop a model capable of automatically detecting and blurring faces and vehicle number plates in photos uploaded through the JAKI app. Utilizing machine learning technology and the Detectron2 library, we aim to create an efficient and effective solution that can be integrated seamlessly with the JakLapor system within the JAKI app.

The "Korean Dramas Analytical Dashboard" is a comprehensive visualization tool crafted using Tableau, integrating data gathered both from online sources and through manual research. This unique dashboard stands out for its inclusion of subjective ratings, personally assigned by the creator, providing a distinctive layer of analysis. By combining web-derived data and manually curated information, the dashboard offers a holistic view of Korean dramas, allowing users to explore trends, patterns, and performance metrics. The inclusion of subjective ratings enhances the user experience, offering a personalized touch to the analysis. This analytical tool is designed to aid stakeholders in making informed decisions related to Korean dramas, from content acquisition to audience engagement strategies.

The “TWICE Face Recognition with Haar Cascade” project is more than a technological achievement; it’s a bridge between K-pop fandom and the advanced realm of computer vision. As we continue to refine and enhance our system, we look forward to exploring new frontiers in idol recognition technology. Together, let’s celebrate the magic of TWICE and embrace the limitless potential of computer vision in the world of K-pop.