Zheng Tong 
- (2024): Deployment strategies for lightweight pavement defect detection using deep learning and inverse perspective mapping. Dans: Automation in Construction, v. 167 (novembre 2024).
- (2023): Effect of existing pavement condition and overlaying strategy on the reflective cracking resistance of asphalt pavement. Dans: Construction and Building Materials, v. 401 (octobre 2023).
- (2023): Evidential transformer for pavement distress segmentation. Dans: Computer-Aided Civil and Infrastructure Engineering, v. 38, n. 16 (3 octobre 2023).
- (2023): End-to-end BIM-based optimization for dual-objective road alignment design with driving safety and construction cost efficiency. Dans: Automation in Construction, v. 151 (juillet 2023).
- (2023): Aging effects on rheological properties of high viscosity modified asphalt. Dans: Journal of Traffic and Transportation Engineering (English Edition), v. 10, n. 2 (avril 2023).
- (2023): In-Time Density Monitoring of In-Place Asphalt Layer Construction via Intelligent Compaction Technology. Dans: Journal of Materials in Civil Engineering (ASCE), v. 35, n. 1 (janvier 2023).
- (2022): Novel Computer Tomography image enhancement deep neural networks for asphalt mixtures. Dans: Construction and Building Materials, v. 352 (octobre 2022).
- (2022): Assessment of the Aging Process of Finished Product–Modified Asphalt Binder and Its Aging Mechanism. Dans: Journal of Materials in Civil Engineering (ASCE), v. 34, n. 8 (août 2022).
- (2022): Construction quality evaluation of asphalt pavement based on BIM and GIS. Dans: Automation in Construction, v. 141 (septembre 2022).
- (2020): Advances of deep learning applications in ground-penetrating radar: A survey. Dans: Construction and Building Materials, v. 258 (octobre 2020).
- (2021): Characterization of hydration and dry shrinkage behavior of cement emulsified asphalt composites using deep learning. Dans: Construction and Building Materials, v. 274 (mars 2021).
- (2018): Convolutional Neural Network for Asphalt Pavement Surface Texture Analysis. Dans: Computer-Aided Civil and Infrastructure Engineering, v. 33, n. 12 (novembre 2018).
- (2020): Pavement defect detection with fully convolutional network and an uncertainty framework. Dans: Computer-Aided Civil and Infrastructure Engineering, v. 35, n. 8 (10 juillet 2020).
- (2018): Autonomous microscopic bunch inspection using region-based deep learning for evaluating graphite powder dispersion. Dans: Construction and Building Materials, v. 173 (juin 2018).
- (2018): Innovative method for recognizing subgrade defects based on a convolutional neural network. Dans: Construction and Building Materials, v. 169 (avril 2018).
- (2020): Pavement-distress detection using ground-penetrating radar and network in networks. Dans: Construction and Building Materials, v. 233 (février 2020).
- (2019): A new method for CF morphology distribution evaluation and CFRC property prediction using cascade deep learning. Dans: Construction and Building Materials, v. 222 (octobre 2019).
- (2019): A novel method for multi-scale carbon fiber distribution characterization in cement-based composites. Dans: Construction and Building Materials, v. 218 (septembre 2019).
- (2017): Recognition, location, measurement, and 3D reconstruction of concealed cracks using convolutional neural networks. Dans: Construction and Building Materials, v. 146 (août 2017).
- (2017): Study on the optimum rice husk ash content added in asphalt binder and its modification with bio-oil. Dans: Construction and Building Materials, v. 147 (août 2017).
- (2017): Innovation for evaluating aggregate angularity based upon 3D convolutional neural network. Dans: Construction and Building Materials, v. 155 (novembre 2017).
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