# Feature Size and Performance

For both training and runtime, each Deep Learning tool will collect image samples that completely cover the extent of the image.

The feature size is directly related to the time required to run, and to a lesser extent, train the tool. A larger feature size is much quicker to process, but larger feature sizes will not be able to "see" or "respond to" small features.

During training, the tool will sample the entire extent of the input image, and it will oversample regions that it determines contain more information.