Research Assistant - Physics of Tennis

Developed a deep learning model to accurately analyze real-time acoustic data from tennis games. Integrated and fine-tuned computer vision techniques for image segmentation and masking, achieving 95% accuracy in detecting tennis balls during gameplay. The system demonstrated robust performance, effectively tracking ball movement under diverse lighting conditions and enhancing real-time game analysis capabilities.