Method for classifying grid equipment based on convolution neural network
A convolutional neural network and power grid equipment technology, which is applied to biological neural network models, instruments, character and pattern recognition, etc., can solve problems such as impracticality and inaccurate test data classification results, and achieve reduction in size and increase in size. Effects of size and accuracy improvement
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[0024] The present invention will be further described below in conjunction with the drawings. The following embodiments are only used to illustrate the technical solutions of the present invention more clearly, and cannot be used to limit the protection scope of the present invention.
[0025] A method for classifying power grid equipment based on convolutional neural network includes the following steps:
[0026] Step 1. Construct training set and test set.
[0027] By taking pictures on the spot, collecting images of six major power grid equipment, 24 images of each category, and divided into training pictures and test pictures according to the ratio of 3:1.
[0028] Step 2: Construct a grid equipment classification label file corresponding to the grid equipment image.
[0029] Each grid equipment image corresponds to a grid equipment classification label document. The grid equipment classification label document stores the reading path and file name of the corresponding grid equipm...
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