Cordyceps sinensis detection method based on self-encoding feature learning
A technology of Cordyceps sinensis and feature learning, applied in the fields of instrument, calculation, character and pattern recognition, etc., can solve the problem that there is no detection method for Cordyceps sinensis, and it has been seen in the literature.
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[0011] The present invention is based on the Cordyceps sinensis detection method of self-encoding feature learning, and its steps are:
[0012] 1. Preparation of samples
[0013] 1) collecting a series of images containing Cordyceps sinensis;
[0014] 2) Extract the sub-blocks containing Cordyceps sinensis and the sub-blocks containing the background, the extraction ratio is 1:10, and scale them to the same size;
[0015] 3) Classify the samples according to the positive and negative sample categories and number them.
[0016] 2. Classification model training
[0017] 1) Shuffle the order of the sample library, use a two-layer stacked self-encoder network for training, and obtain the model parameters after training;
[0018] 2) Encode the sample library using the trained model,
[0019] 3) At the same time, the code and the sample category label are brought into the nonlinear kernel support vector machine for training to obtain the classification model parameters, wherein ...
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Abstract
Description
Claims
Application Information
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