CPC G06F 18/217 (2023.01) [G06F 18/23213 (2023.01); G06N 3/08 (2013.01)] | 17 Claims |
1. A method of training an image classification model, the method comprising:
maintaining a plurality of ground-penetrating radar (GPR) images captured by a GPR in a database;
establishing a feature value extraction model by primarily learning training data comprising a GPR image in the database and a representative feature value determined as one of feature values of the GPR image, wherein the feature value extraction model is a first model that outputs a feature value set of a new GPR image input to an image classification model;
inputting a GPR image to the feature value extraction model and acquiring a feature value set of the GPR image output from the feature value extraction model; and
establishing a feature value classification model by secondarily learning training data comprising the acquired feature value set of the GPR image and a label value to which the GPR image is classified, wherein the feature value classification model is a second model that outputs a label value of the new GPR image as a result value of the image classification model.
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