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Visualize and Verify Deep Neural Networks

Visualize network behavior, explain predictions, and verify robustness

Visualize deep networks during and after training. Monitor training progress using built-in plots of network accuracy and loss, or by specifying custom metrics. Investigate trained networks using visualization and interpretability techniques such as Grad-CAM, occlusion sensitivity, LIME, deep dream, and D-RISE.

You can use the Deep Network Designer app to interactively build and visualize deep learning networks. You can then generate code to recreate network construction and export trained networks to Simulink®.

Use deep learning verification methods to assess the properties of deep neural networks. For example, you can verify the robustness properties of a network, compute network output bounds, find adversarial examples, and detect out-of-distribution data.