Fangyu Liu
- (2024): Multiple-type distress detection in asphalt concrete pavement using infrared thermography and deep learning. In: Automation in Construction, v. 161 (May 2024).
- (2024): Transfer learning-based encoder-decoder model with visual explanations for infrastructure crack segmentation: New open database and comprehensive evaluation. In: Underground Space, v. 17 (August 2024).
- (2023): Involving prediction of dynamic modulus in asphalt mix design with machine learning and mechanical-empirical analysis. In: Construction and Building Materials, v. 407 (December 2023).
- (2024): Exploring the mechanism of micro-nano bubble water in enhancing the mechanical properties of sulfoaluminate cement-based materials. In: Construction and Building Materials, v. 411 (January 2024).
- (2023): PI-LSTM: Physics-informed long short-term memory network for structural response modeling. In: Engineering Structures, v. 292 (October 2023).
- (2022): Asphalt pavement fatigue crack severity classification by infrared thermography and deep learning. In: Automation in Construction, v. 143 (November 2022).
- (2022): Improving asphalt mix design considering international roughness index of asphalt pavement predicted using autoencoders and machine learning. In: Construction and Building Materials, v. 360 (December 2022).
- (2022): Optimizing asphalt mix design through predicting the rut depth of asphalt pavement using machine learning. In: Construction and Building Materials, v. 356 (November 2022).
- (2022): Improving asphalt mix design by predicting alligator cracking and longitudinal cracking based on machine learning and dimensionality reduction techniques. In: Construction and Building Materials, v. 354 (November 2022).
- (2022): UNet-based model for crack detection integrating visual explanations. In: Construction and Building Materials, v. 322 (March 2022).
- (2022): Deep learning and infrared thermography for asphalt pavement crack severity classification. In: Automation in Construction, v. 140 (August 2022).
- (2022): Deep transfer learning-based vehicle classification by asphalt pavement vibration. In: Construction and Building Materials, v. 342 (August 2022).
- (2022): Optimizing asphalt mix design through predicting effective asphalt content and absorbed asphalt content using machine learning. In: Construction and Building Materials, v. 325 (March 2022).
- (2020): An artificial neural network model on tensile behavior of hybrid steel-PVA fiber reinforced concrete containing fly ash and slag power. In: Frontiers of Structural and Civil Engineering, v. 14, n. 6 (August 2020).
- (2020): Experimental investigation on the tensile behavior of hybrid steel-PVA fiber reinforced concrete containing fly ash and slag powder. In: Construction and Building Materials, v. 241 (April 2020).
- (2019): Experimental investigation on the flexural behavior of hybrid steel-PVA fiber reinforced concrete containing fly ash and slag powder. In: Construction and Building Materials, v. 228 (December 2019).
- (2019): An experimental investigation on the integral waterproofing capacity of polypropylene fiber concrete with fly ash and slag powder. In: Construction and Building Materials, v. 212 (July 2019).
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