In this paper, we propose a hybrid approach which combines deep learning and Bayesian probability for robust crack detection in images in real-time. We propose ...

In this paper, we propose a novel hybrid approach for crack detection in raw images, which combines deep learning models and Bayesian probabilistic analysis for ...

The proposed CNN model is a novel approach to detecting cracks on low pixel density images of concrete surfaces for its economic and processing efficiency ...

The present hybrid approach DO-YOLOv4-IPTs outperforms the widely used Convolutional Neural Network (CNN)-based crack segmentation methods with less labeling ...

In this paper, we propose a novel hybrid approach for crack detection in raw images, which combines deep learning models and Bayesian probabilistic analysis for ...

Feb 29, 2024 · To address these problems, the Deformable Oriented YOLOv4 (DO-YOLOv4) is first developed for crack detection based on the traditional YOLOv4, in ...

Article,. A novel hybrid approach for crack detection. F. Fang, L. Li, Y.

Sep 4, 2024 · Introduce the Hybrid-Segmentor model to efficiently detect cracks in infrastructures, which is based on the encoder-decoder architecture that ...

In this study, the proposed approach offers a novel hybrid image-based deep learning method for autonomous concrete fracture identification.

Aug 9, 2021 · In this paper, the deep learning method is used to intelligently identify microcracks in the microscopic morphology of SEM image.