Course: Machine Learning (Fall 2022)
Task: Generate explanations for the classification results by ResNet50 using Grad-CAM and LIME. Implement with https://keras.io/examples/vision/grad_cam/ and https://github.com/marcotcr/lime
Pre-trained model that was used:
- ResNet50 Model
Explanation AI used:
- Grad-CAM
- LIME
The Grad-CAM highlights the localized areas on the image that contributes positively to the model’s classification.
The LIME explanation method visualizes the contribution of each feature of an image to the model’s classification.
Conclusion, that the ResNet50 model can correctly identify and focus on the right areas of the image to make its classification