Created a chess-playing game that could predict optimal moves for both human players and computer opponents, ensuring the first player had a high chance of winning. Implemented a node-based system for recording information about each game board, including parents, children, and paths; optimized efficiency and reduced processing time by 30% through Alpha-beta pruning
- Demo Video
- Try on Replit (Recommend zooming out your screen.)
Using JavaScript WebGL/OpenGL to draw all objects in 3D space. Using HTML/CSS to present the interface. In addition, each planet can reflect the environment. The viewpoint of players and background can be moved and rotated, the music starts as the game starts, and players have to reach the end of the maze without touching obstacles to pass the level. The game has two levels.
Using Canny detector-Hough transform and define edges to calculate the slopes and the intercepts. Visualized and recognized objects in real-time from the perspective of an electric vehicle.
To solve the problem of recognizing many members of Korean groups, it uses face recognition technology to help the director recognize people in a short time. Using Haar Cascade from OpenCV to train the face model and inferred face model in Python.