Denial radiography

Developed a deep learning project for dental radiography analysis using Convolutional Neural Networks (CNN). The model was first built and trained from scratch to understand feature extraction from dental X-ray images and to classify dental conditions accurately.

After evaluating performance, a pre-trained model (transfer learning approach) was implemented to improve accuracy and reduce training time. Fine-tuning techniques were applied to adapt the model to the dental dataset, achieving better generalization and higher performance compared to the model built from scratch.

This project demonstrates strong knowledge of deep learning, medical image processing, CNN architecture design, and transfer learning techniques.