Jia Liang
- (2024): Small-sample data-driven lightweight convolutional neural network for asphalt pavement defect identification. In: Case Studies in Construction Materials, v. 21 (Dezember 2024).
- (2024): Forecasting the cost premium of certified green building in China: A cutting-edge methodology incorporating radial basis function neural network and various optimization algorithms. In: Energy and Buildings, v. 317 (August 2024).
- (2024): CNN-based network with multi-scale context feature and attention mechanism for automatic pavement crack segmentation. In: Automation in Construction, v. 164 (August 2024).
- (2023): Modified fractional-Zener model—Numerical application in modeling the behavior of asphalt mixtures. In: Construction and Building Materials, v. 388 (Juli 2023).
- (2024): Lightweight convolutional neural network driven by small data for asphalt pavement crack segmentation. In: Automation in Construction, v. 158 (Februar 2024).
- (2023): Application of a stochastic damage model to predict the variability of creep behavior for asphalt mixtures. In: Case Studies in Construction Materials, v. 18 (Juli 2023).
- (2022): Experimental and analytical methods for evaluating the high temperature viscoelastic properties of fine aggregate matrix. In: Materials and Structures, v. 55, n. 7 (5 August 2022).
- (2022): Automatic extraction and evaluation of pavement three-dimensional surface texture using laser scanning technology. In: Automation in Construction, v. 141 (September 2022).
- (2020): Fast and robust pavement crack distress segmentation utilizing steerable filtering and local order energy. In: Construction and Building Materials, v. 262 (November 2020).
- (2020): Development and application of a non-destructive pavement testing system based on linear structured light three-dimensional measurement. In: Construction and Building Materials, v. 260 (November 2020).
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