Project Results and Assessment

After training both the ANN and CNN models, the next step is to evaluate their performance and interpret the results. This module summarizes the outputs generated during the project and highlights the improvements achieved by using a Convolutional Neural Network for image classification.

The results help learners understand how deep learning models perform and why CNNs are widely used for computer vision applications.

After completing the project, several outputs are generated that demonstrate the performance of both models.

The outputs include:

Dataset Visualization

Displays sample images from the CIFAR-10 dataset.

Preprocessed Images

Shows the normalized image data used for training.

ANN Performance

Displays the training and testing accuracy of the Artificial Neural Network.

CNN Performance

Displays the training and testing accuracy of the Convolutional Neural Network.

Image Predictions

Predicts the class labels for unseen test images.

Model Comparison

Compares the performance of the ANN and CNN models.

These outputs help evaluate how effectively each model classifies images.