Person Classification System

Training deep learning models typically requires massive datasets. This project faced the challenge of building an accurate classifier with severely limited labeled images per person.

Solution

Leveraged transfer learning with pre-trained convolutional neural networks, fine-tuned for the specific domain. Applied strategic data augmentation to overcome dataset limitations and achieved 98% validation accuracy.