stem/AI/Neural Networks/CNN/Interpretation.md
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# Activation Maximisation
- Synthesise an ideal image for a class
- Maximise 1-hot output
- Maximise [[Activation Functions#SoftMax|SoftMax]]
![[am.png]]
- **Use trained network**
- Don't update weights
- [[Architectures|Feedforward]] noise
- [[Back-Propagation|Back-propagate]] [[Deep Learning#Loss Function|loss]]
- Don't update weights
- Update image
![[am-process.png]]
## Regulariser
- Fit to natural image statistics
- Prone to high frequency noise
- Minimise
- Total variation
- $x^*$ is the best solution to minimise [[Deep Learning#Loss Function|loss]]