AI & ML
Face Recognition
Enrollment, match, and metrics you can defend.
Structured for ML vivas: dataset notes, train/val split, metrics, and failure cases. Emphasizes responsible use and consent language for academic settings.
Highlights
- Enrollment gallery workflow
- Threshold tuning narrative
- Live webcam demo script
Suggested stack
- Python
- OpenCV / face_recognition / ONNX
- NumPy
- Optional Flask UI
Deliverables
- Synopsis
- Training & inference scripts
- Labeled dataset guidance
- Results tables & plots
- Conclusion + limitation paragraph set