Developed a web-based real-time face recognition application to assist instructors in recognizing students' faces through a user-friendly interface.
Integrated React.js frontend for image capturing with backend facial recognition capabilities.
Contributed to the stored face management interface, enabling face classification, and facilitated integration of processed face images with their labeled names from the backend database.
Developed the user authentication backend with Node.js/express.js to receive input from the frontend, authenticate passphrase and user name inputs, as well as handle input errors.
Developed a GIS navigation system with C++, built data structures using combinations of C++ STL maps and vectors for different purposes (Applied Dijkstra and A* Algorithms to find the shortest path between two locations).
Used Libcurl to incorporate real-time data. Achieved auto-correction function of the search bar, Designed the user interface of the GIS navigation system.
The work is protected by the Academic Integrity Guideline of University of Toronto
FLShape Project - Adaptive Makeup Recommender
University of Toronto (Sep 2020 - Dec 2020)
Developed a program with Python to identify diverse facial shapes, optimizing makeup matches based on distinct characteristics such as eyebrow shape and blush positioning.
Trained models on 6k+ facial images categorized into six foundational face shapes. Achieved a training accuracy of 0.890 and a validation accuracy of 0.781. Used ResNet as the basic framework, optimizing shorter effective paths to maintain high accuracy even with increased layer complexity.
Developed a strategy game- Treasure Island with Verilog, which includes game logic and interrupts. PS/2 controls are applied to control the operation of the game while connected to a VGA display.