Recognition method of bridge apparent defects based on image processing and improved convolutional neural networks.

ABSTRACT: As an important transportation hub, the detection of appearance defects in bridges has been characterized by low accuracy and low efficiency. To address this problem, the study proposes a bridge appearance defect recognition model based on image processing and improved convolutional neural network. The model is divided into three different modules. The first module is the bridge appearance defect classification and recognition module based on transfer learning and convolutional network. The second module further localizes the region of defective cracks based on the classification and recognition results. This module uses improved fast region convolutional neural network for region segmentation to further determine the location of cracks in the image. Finally, operations such as corrosion a

SUBMITTER: Li S 

PROVIDER: S-EPMC12617900 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature