Introduction - If you have any usage issues, please Google them yourself
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The first step: Training Network. The use of training samples for training.
Step two: identification. First, open the image (256 colors) again, normalized to deal with, click on the "one-time deal" Finally, click "R" or use the menu to find the corresponding items to be identified. Recognition results show up on the screen, but also output to a file Result.txt Medium.
The system s recognition rate under normal circumstances was 90 .
Alternatively, you could open a separate picture of the image pre-processing step by step job, but bearing in mind that each step can only run job again, but according to the order of implementation.
Concrete steps as: "256-color bitmap to grayscale"- "two grayscale values of"- "De-noising"- "tip-tilt correction"- "split"- "the standardization of size"- "tight rearrangement."
Note that to be identified with the picture win.dat and whi.dat located in the same directory, these two files after training the weights of the netw