Duo Ma
- (2023): Study on the shear strength and damage constitutive model of the contact surface between PVA fiber-enhanced cement mortar and concrete. In: Construction and Building Materials, v. 400 (Oktober 2023).
- (2024): An automatic defect classification and segmentation method on three-dimensional point clouds for sewer pipes. In: Tunnelling and Underground Space Technology, v. 143 (Januar 2024).
- (2023): Defects identification and location of underground space for ground penetrating radar based on deep learning. In: Tunnelling and Underground Space Technology, v. 140 (Oktober 2023).
- (2023): A low-cost 3D reconstruction and measurement system based on structure-from-motion (SFM) and multi-view stereo (MVS) for sewer pipelines. In: Tunnelling and Underground Space Technology, v. 141 (November 2023).
- (2023): 3D reconstruction and segmentation system for pavement potholes based on improved structure-from-motion (SFM) and deep learning. In: Construction and Building Materials, v. 398 (September 2023).
- (2023): Transformer‐optimized generation, detection, and tracking network for images with drainage pipeline defects. In: Computer-Aided Civil and Infrastructure Engineering, v. 38, n. 15 (April 2023).
- (2022): Automatic defogging, deblurring, and real-time segmentation system for sewer pipeline defects. In: Automation in Construction, v. 144 (Dezember 2022).
- (2022): Automatic damage segmentation in pavement videos by fusing similar feature extraction siamese network (SFE-SNet) and pavement damage segmentation capsule network (PDS-CapsNet). In: Automation in Construction, v. 143 (November 2022).
- (2022): Innovative method for pavement multiple damages segmentation and measurement by the Road-Seg-CapsNet of feature fusion. In: Construction and Building Materials, v. 324 (März 2022).
- (2021): A Multi-defect detection system for sewer pipelines based on StyleGAN-SDM and fusion CNN. In: Construction and Building Materials, v. 312 (Dezember 2021).
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