Digital Identification System
2016-08-23
0 0 0
4.0
Other
Earn points
Instructions for use:
The first step: training network. Using the training samples for training. (This program may not training because I have to save up the trained network parameters, when the reader can be used in direct recognition)
Step Two: Identify.
First, open the image (256 colors)
Again, a normalization process. Click the "one-time deal."
Finally, click on the "R" or use the menu to find the corresponding item to be identified
Recognition results are displayed on the screen, but also in the output to a file result.txt
Recognition rate of the system is generally 90%
Alternatively, you can open a single picture of an image preprocessing step by step. But pay attention to every step of the work can only be performed again, and executed according to the order. Steps as follows: "256-color bitmap into
The first step: training network. Using the training samples for training. (This program may not training because I have to save up the trained network parameters, when the reader can be used in direct recognition)
Step Two: Identify.
First, open the image (256 colors)
Again, a normalization process. Click the "one-time deal."
Finally, click on the "R" or use the menu to find the corresponding item to be identified
Recognition results are displayed on the screen, but also in the output to a file result.txt
Recognition rate of the system is generally 90%
Alternatively, you can open a single picture of an image preprocessing step by step. But pay attention to every step of the work can only be performed again, and executed according to the order. Steps as follows: "256-color bitmap into
c++
识别
系统
数字
Related Source Codes
Local Path Planning Algorithm - DWA Algorithm
0
0
no vote
enDAQ-Shock-Data-Share-SRS-Blog
0
0
no vote
Calling chatGPT in a Windows application
0
0
no vote
Test Hello world
0
0
no vote
RCS calculation by one-way ray tracing
0
0
no vote
No comment