project 12
ResNet50 & VGG19 Model Comparison
An analytical study training classic convolutional architectures on a custom dataset through transfer learning, then benchmarking their accuracy and inference speed.
- Category
- AI
technologies used
- Python
- TensorFlow
- Keras
- CUDA
- Matplotlib
- Seaborn
key features
- 01Fine-tuning strategies with layer-wise weight freezing and custom classification heads.
- 02Architecture performance comparison across precision, recall and F1-score metrics.
- 03Training loops optimised with CUDA acceleration.