Real-time detection of cars and sidelights using custom YOLOv5 model with 95% mAP accuracy.
Developed a custom YOLOv5 object detection model for real-time detection of cars and sidelights, achieving 95% mean Average Precision (mAP). The model was integrated into the CarSight prototype for automated driving test evaluation, significantly improving the accuracy and efficiency of driving assessments.
AI-based gait analysis using deep learning and signal processing for motion understanding....
Character-level music generation using LSTM-based RNNs trained on symbolic music data....
Implemented CNNs and DB-VAE for bias mitigation in facial detection systems....