Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 43, 2026 No. 7
2204-2211

GSDI-VMunet: Mamba-based network for concrete crack

Xu Shengjun1a,2
Yang Pengyu1a,2
Ren Rui1b
Li Zhijie1a
Xin Ren1c
Shi Ya1a
1. a. College of Information and Control Engineering, b. Institute for Interdisciplinary Innovation Research, c. College of Civil Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
2. Key Laboratory of Intelligent Automation Technology for Building Manufacturing, Xi'an 710055, China
DOI: 10.19734/j.issn.1001-3695.2025.11.0473

Abstract

Deep learning-based concrete crack segmentation plays a critical role in structural health monitoring. However, exi-sting methods remain limited by weak robustness under complex background interference and insufficient accuracy in fine crack segmentation. To address these limitations, this study proposed a GSDI-VMunet network for concrete crack segmentation. Firstly, it introduced a gated semantic and detail interaction(GSDI) module to mitigate feature mismatch between deep semantic features and shallow detail features during multi-level fusion. Secondly, it designed a reshape-convolution-gating mechanism to suppress information redundancy and enhance discriminative feature representation during feature fusion. Thirdly, it constructed a lightweight encoder-decoder architecture based on a four-level cascaded implicit multi-granularity feature pyramid. PatchExpanding upsampling was further integrated to improve pixel-level crack topology reconstruction. Experimental results on the CRACK500 and CFD benchmark datasets show that GSDI-VMunet achieves mIoU values of 81.88% and 83.14%, and F1-scores of 79.79% and 80.25%, respectively. These results demonstrate that the proposed network provides improved accuracy and robustness for concrete crack segmentation under complex conditions.

Foundation Support

国家自然科学基金面上项目(62476211,52478204)
陕西省自然科学基础研究计划(2024JC-YBMS-483,2023-JC-YB-532,2025JC-YBMS-792)
陕西省教育厅协同创新中心项目(23JY038)
西安市碑林区科技局项目(GX2423)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.11.0473
Publish at: Application Research of Computers Printed Article, Vol. 43, 2026 No. 7
Section: Technology of Graphic & Image
Pages: 2204-2211
Serial Number: 1001-3695(2026)07-035-2204-08

Publish History

[2026-03-25] Accepted Paper
[2026-07-05] Printed Article

Cite This Article

徐胜军, 杨朋于, 任瑞, 等. GSDI-VMunet:基于Mamba结构的混凝土裂缝分割网络 [J]. 计算机应用研究, 2026, 43 (7): 2204-2211. (Xu Shengjun, Yang Pengyu, Ren Rui, et al. GSDI-VMunet: Mamba-based network for concrete crack [J]. Application Research of Computers, 2026, 43 (7): 2204-2211. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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