EGC image classification method based on CNN + SVM
A classification method and image technology, applied in neural learning methods, instruments, biological neural network models, etc., can solve problems such as hidden safety hazards and poor classification effects, and achieve a solution with reduced safety hazards, high accuracy, and high interpretability. Effect
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[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0024] A CNN+SVM-based EGC image classification method, such as figure 1 shown, including the following steps:
[0025] Step 1. Data preprocessing: convert all data into grayscale images, omit sample color information, increase image contrast, and normalize the data converted into grayscale images to obtain the original data set;
[0026] Step 2. Data division: divide the data set to obtain training set and test set;
[0027] Step 3, data feature extraction:...
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