- Automated detection of through-cracks in pavement using three-instantaneous attributes fusion and Swin Transformer network. In: Automation in Construction, v. 158 (February 2024). (2024):
- A coarse aggregate gradation detection method based on 3D point cloud. In: Construction and Building Materials, v. 377 (May 2023). (2023):
- Evaluation and Comparison of Real-Time Laser and Electric Sand-Patch Pavement Texture-Depth Measurement Methods. In: Journal of Transportation Engineering, v. 142, n. 7 (July 2016). (2016):
- Assessment of importance-based machine learning feature selection methods for aggregate size distribution measurement in a 3D binocular vision system. In: Construction and Building Materials, v. 306 (November 2021). (2021):
- Asphalt Pavement Friction Coefficient Prediction Method Based on Genetic-Algorithm-Improved Neural Network(GAI-NN) Model. In: Canadian Journal of Civil Engineering / Revue canadienne de génie civil, v. 49, n. 1 (January 2022). (2022):
- Quantitative evaluation for shape characteristics of aggregate particles based on 3D point cloud data. In: Construction and Building Materials, v. 263 (December 2020). (2020):
- Pavement aggregate shape classification based on extreme gradient boosting. In: Construction and Building Materials, v. 256 (September 2020). (2020):