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The following bibliography contains all publications indexed in this database that are linked with this name as either author, editor or any other kind of contributor.

  1. Ma, Duo / Wang, Niannian / Fang, Hongyuan / Chen, Weiwei / Li, Bin / Zhai, Kejie: Attention‐optimized 3D segmentation and reconstruction system for sewer pipelines employing multi‐view images. In: Computer-Aided Civil and Infrastructure Engineering.

    https://doi.org/10.1111/mice.13241

  2. Zhang, Xijun / Du, Mingrui / Fang, Hongyuan / Li, Bin / Zhao, Peng / Zhai, Kejie / Yao, Xupei / Du, Xueming / Shi, Mingsheng / Ma, Duo (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 (October 2023).

    https://doi.org/10.1016/j.conbuildmat.2023.132571

  3. Wang, Niannian / Ma, Duo / Du, Xueming / Li, Bin / Di, Danyang / Pang, Gaozhao / Duan, Yihang (2024): An automatic defect classification and segmentation method on three-dimensional point clouds for sewer pipes. In: Tunnelling and Underground Space Technology, v. 143 (January 2024).

    https://doi.org/10.1016/j.tust.2023.105480

  4. Hu, Haobang / Fang, Hongyuan / Wang, Niannian / Ma, Duo / Dong, Jiaxiu / Li, Bin / Di, Danyang / Zheng, Hongbiao / Wu, Jiang (2023): Defects identification and location of underground space for ground penetrating radar based on deep learning. In: Tunnelling and Underground Space Technology, v. 140 (October 2023).

    https://doi.org/10.1016/j.tust.2023.105278

  5. Ma, Duo / Fang, Hongyuan / Wang, Niannian / Pang, Gaozhao / Li, Bin / Dong, Jiaxiu / Jiang, Xue (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).

    https://doi.org/10.1016/j.tust.2023.105345

  6. Wang, Niannian / Dong, Jiaxiu / Fang, Hongyuan / Li, Bin / Zhai, Kejie / Ma, Duo / Shen, Yibo / Hu, Haobang (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).

    https://doi.org/10.1016/j.conbuildmat.2023.132499

  7. Ma, Duo / Fang, Hongyuan / Wang, Niannian / Lu, Hongfang / Matthews, John / Zhang, Chao (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).

    https://doi.org/10.1111/mice.12970

  8. Ma, Duo / Fang, Hongyuan / Wang, Niannian / Zheng, Hangwei / Dong, Jiaxiu / Hu, Haobang (2022): Automatic defogging, deblurring, and real-time segmentation system for sewer pipeline defects. In: Automation in Construction, v. 144 (December 2022).

    https://doi.org/10.1016/j.autcon.2022.104595

  9. Dong, Jiaxiu / Wang, Niannian / Fang, Hongyuan / Wu, Rui / Zheng, Chengzhi / Ma, Duo / Hu, Haobang (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).

    https://doi.org/10.1016/j.autcon.2022.104537

  10. Dong, Jiaxiu / Wang, Niannian / Fang, Hongyuan / Hu, Qunfang / Zhang, Chao / Ma, Baosong / Ma, Duo / Hu, Haobang (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 (March 2022).

    https://doi.org/10.1016/j.conbuildmat.2022.126719

  11. Ma, Duo / Liu, Jianhua / Fang, Hongyuan / Wang, Niannian / Zhang, Chao / Li, Zhaonan / Dong, Jiaxiu (2021): A Multi-defect detection system for sewer pipelines based on StyleGAN-SDM and fusion CNN. In: Construction and Building Materials, v. 312 (December 2021).

    https://doi.org/10.1016/j.conbuildmat.2021.125385

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