Deep learning-based tunnel lining disease intelligent detection method

• Main Authors: LI MEIKANG, ZHU QIANWEN, TU XINYUE
• Format: Patent
• Language: Chinese; English
• Published: 12.07.2022
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; HANDLING RECORD CARRIERS; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS

The invention discloses a tunnel lining disease intelligent detection method based on deep learning. The method comprises the steps that S1, a tunnel lining disease data set composed of marked disease image samples is made; s2, dividing disease image samples in the tunnel lining disease data set into a training set and a test set; s3, building a deep learning model; s4, training and parameter iteration are carried out on the built deep learning model through the training set, the detection effect of the trained deep learning model is evaluated through the test set, and the finally applied deep learning model is selected; and S5, detecting diseases in the tunnel image by using the selected deep learning model, and outputting disease category and position information. The tunnel image is used as a data source, the tunnel apparent diseases are intelligently identified and classified through the deep learning model, the disease positions are positioned, and the working efficiency is greatly improved compared with