Training of Neural Network

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Training of Neural Network

Training of the neural network can be performed in three different ways represented by the three buttons at the bottom of the dialog window:


1.The Train Network button directly starts the configured training locally. Note that only the samples selected in the 3. Samples list will be used for the training. As a result, the weights and manifest files will be updated.

2.When activating Export R workspace, the configured preprocessing operations are applied to the selected data and the resulting images are exported together with the training configuration in the form of a compact R workspace. The workspace can then be transferred to a more powerful processing environment for the actual training. This can either be another PMOD installation on a more powerful machine or in the cloud.

3.The Train Network with Workspace button opens a dialog window for loading a previously exported R workspace and starts the training locally.


After completion of the training, the resulting Weights and Manifest files can be transferred, along with the definition of the model if necessary, to other PMOD installations for prediction.


On typical personal computers local training is only recommended for tests with a limited amount of data. Even for powerful workstations, training with hundreds of samples may take many hours. Training on a cloud computing infrastructure with virtual machines accessing several GPUs is likely to be more time- and cost-efficient.