The main goals of this project are as listed below:
- Implement and understand CNN architecture, specifically LeNet5
- Training the convolutional nerual network on MNIST, Fashion MNIST and CIFAR 10 dataset
- Network parameters (learning rate, momentum, training batch size) tuning
- Evaluation and Ablation study: Analyze Receiver Operating characteristic Curve (ROC) and Area under curve (AUC) metrics
- Analyse classification performance on noisy data (by intrducing symmetric label noise)
Please consult the problem statement and project report documents for more details