Subway tunnel disease detection method based on deep learning
A tunnel disease and deep learning technology, applied in the field of image processing and deep learning, can solve problems such as time-consuming, inefficient, and slow manual inspection, and achieve the effect of improving representativeness and good results
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[0037] The present invention is described in further detail now in conjunction with accompanying drawing.
[0038] It should be noted that terms such as "upper", "lower", "left", "right", "front", and "rear" quoted in the invention are only for clarity of description, not for Limiting the practicable scope of the present invention, and the change or adjustment of the relative relationship shall also be regarded as the practicable scope of the present invention without substantive changes in the technical content.
[0039] The present invention recognizes and learns a large amount of subway tunnel surface image information through the deep neural network technology, realizes accurate positioning and classification of different tunnel diseases, and then performs disease detection and evaluation on the identified tunnel surface areas. figure 1 The general workflow of the subway tunnel defect detection method based on deep learning is shown.
[0040] Step S10 , creating an image ...
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