Figure 4


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Training progress of both Model-NN and Actor-NN. Experimental data (i.e. SLM phase masks and intensity camera images) is used for the Model-NN, while EMNIST data base is used for the Actor-NN. We used 2k data each, where 1600 samples are used for training and 400 for test, respectively. Both NNs comprise of a single-layer structure with sigmoid activation function. MSE is used as loss function with adam optimizer, wheres fidelity is used as performance indicator. Convergence is observed in all scenarios that are training (solid) and test data (dashed) for Model-NN (red) and Actor-NN (blue), respectively.

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